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Applications of artificial neural networks in chemical engineering
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/aic.690160626openalex-snapshot
Optimal stochastic control of nonlinear systems
inferredcites →https://doi.org/10.1002/aic.690351106openalex-snapshot
Incipient fault diagnosis of chemical processes via artificial neural networks
inferredcites →https://doi.org/10.1002/aic.690360703openalex-snapshot
Robust error‐in‐variables estimation using nonlinear programming techniques
inferredcites →https://doi.org/10.1002/aic.690370112openalex-snapshot
Fault diagnosis in complex chemical plants using artificial neural networks
inferredcites →https://doi.org/10.1002/aic.690381003openalex-snapshot
A hybrid neural network‐first principles approach to process modeling
inferredcites →https://doi.org/10.1002/aic.690400510openalex-snapshot
Diagnosis of multiple simultaneous fault via hierarchical artificial neural networks
inferredcites →https://doi.org/10.1002/aic.690401110openalex-snapshot
Dynamic data rectification by recurrent neural networks vs. Traditional methods
inferredcites →https://doi.org/10.1002/aic.690411019openalex-snapshot
Neural model‐predictive control of distributed parameter crystal growth process
inferredcites →https://doi.org/10.1002/aic.690420215openalex-snapshot
Predictive control of quality in batch polymerization using hybrid ANN models
inferredcites →https://doi.org/10.1002/aic.690420812openalex-snapshot
Dynamic rectification of data via recurrent neural nets and the extended Kalman filter
inferredcites →https://doi.org/10.1002/aic.690441009openalex-snapshot
Active learning from process data
inferredcites →https://doi.org/10.1002/aic.690450806openalex-snapshot
Neural‐network modeling and optimization of induced foreign protein production
inferredcites →https://doi.org/10.1002/ceat.270190307openalex-snapshot
Hybrid knowledge‐based tool for mixing equipment selection – the fuzzy neural network
inferredcites →https://doi.org/10.1002/cjce.5450720308openalex-snapshot
Neural network based objective flow regime identification in air‐water two phase flow
inferredcites →https://doi.org/10.1002/cjce.5450730604openalex-snapshot
Modelling of induced aeration in turbine aerators by use of radial basis function neural networks
inferredcites →https://doi.org/10.1002/cjce.5450750311openalex-snapshot
Arma neuron networks for modeling nonlinear dynamical systems
inferredcites →https://doi.org/10.1007/978-1-4615-3954-4openalex-snapshot
Structure Level Adaptation for Artificial Neural Networks
inferredcites →https://doi.org/10.1007/978-3-642-79119-2_7openalex-snapshot
Prediction Risk and Architecture Selection for Neural Networks
inferredcites →https://doi.org/10.1007/bf02075461openalex-snapshot
Convergence properties of radial basis functions
inferredcites →https://doi.org/10.1007/bf02551274openalex-snapshot
Approximation by superpositions of a sigmoidal function
inferredcites →https://doi.org/10.1007/bfb0104281openalex-snapshot
Neural networks for protein structure prediction
inferredcites →https://doi.org/10.1016/0005-1098(81)90018-2openalex-snapshot
Identification of stochastic linear systems in presence of input noise
inferredcites →https://doi.org/10.1016/0009-2509(93)81009-kopenalex-snapshot
A generalized neural-net kinetic rate equation
inferredcites →https://doi.org/10.1016/0019-0578(92)90123-zopenalex-snapshot
The application neural networks in the process industry
inferredcites →https://doi.org/10.1016/0019-0578(93)90066-6openalex-snapshot
Practical applications of artificial neural networks in chemical process development
inferredcites →https://doi.org/10.1016/0098-1354(88)87015-7openalex-snapshot
Artificial neural network models of knowledge representation in chemical engineering
inferredcites →https://doi.org/10.1016/0098-1354(92)80045-bopenalex-snapshot
Process control via artificial neural networks and reinforcement learning
inferredcites →https://doi.org/10.1016/0098-1354(93)80091-zopenalex-snapshot
Neural network frames. Application to biochemical kinetic diagnosis
inferredcites →https://doi.org/10.1016/0098-1354(93)80259-popenalex-snapshot
A neural network model for analysis and optimization of processes
inferredcites →https://doi.org/10.1016/0098-1354(94)00098-9openalex-snapshot
Modeling and control of a packed distillation column using artificial neural networks
inferredcites →https://doi.org/10.1016/0098-1354(94)80011-1openalex-snapshot
Artificial neural networks as a predictive tool for vapor-liquid equilibrium
inferredcites →https://doi.org/10.1016/0098-1354(94)80102-9openalex-snapshot
Modeling and control by artificial neural networks in biotechnology
inferredcites →https://doi.org/10.1016/0098-1354(94)e0025-iopenalex-snapshot
Some practical insights into neural network implementation in metallurgical industry
inferredcites →https://doi.org/10.1016/0098-1354(94)e0026-jopenalex-snapshot
Neural network models for final process time determination in fermented milk production
inferredcites →https://doi.org/10.1016/0098-1354(94)e004h-zopenalex-snapshot
Neural networks for process analysis and optimization: Modeling and applications
inferredcites →https://doi.org/10.1016/0098-1354(95)00193-xopenalex-snapshot
Rectification of data in a dynamic process using artificial neural networks
inferredcites →https://doi.org/10.1016/0098-1354(95)00243-xopenalex-snapshot
Resolving problems in closed loop nonlinear process identification using IRN
inferredcites →https://doi.org/10.1016/0098-1354(95)87123-3openalex-snapshot
Flow of information through an artificial neural network
inferredcites →https://doi.org/10.1016/0098-1354(95)87124-1openalex-snapshot
Dynamic process diagnosis via integrated neural networks
inferredcites →https://doi.org/10.1016/0098-1354(95)87131-4openalex-snapshot
Mathematical modeling of liquid - liquid equlibria in aqueous polymer solution containing neutral proteinase and oxytetracycline using artificial neural network
inferredcites →https://doi.org/10.1016/0098-1354(95)87133-0openalex-snapshot
Monitoring and control of hydrometallurgical processes with self-organizing and adaptive neural net systems
inferredcites →https://doi.org/10.1016/0098-1354(96)00060-9openalex-snapshot
Use of neural networks for predicting the performance of discontinuous gas-solid chilling machines
inferredcites →https://doi.org/10.1016/0098-1354(96)00078-6openalex-snapshot
Feature correlation method for enhancing fermentation development: A comparison of quadratic regression with artificial neural networks
inferredcites →https://doi.org/10.1016/0098-1354(96)00096-8openalex-snapshot
Use of neural networks for LPCVD reactors modelling
inferredcites →https://doi.org/10.1016/0098-1354(96)00125-1openalex-snapshot
Hybrid neural model of thermal drying in a fluidized bed
inferredcites →https://doi.org/10.1016/0098-1354(96)00133-0openalex-snapshot
A comparison of recurrent training algorithms for time series analysis and system identification
inferredcites →https://doi.org/10.1016/0098-1354(96)00156-1openalex-snapshot
Analysis of plant measurements through input-training neural networks
inferredcites →https://doi.org/10.1016/0098-1354(96)00190-1openalex-snapshot
Visualisation of plant disturbances using self-organising maps
inferredcites →https://doi.org/10.1016/0098-1354(96)00193-7openalex-snapshot
Intelligent manufacturing of polymers
inferredcites →https://doi.org/10.1016/0893-6080(94)90014-0openalex-snapshot
Introduction to the theory of neural computation
inferredcites →https://doi.org/10.1016/0959-1524(95)00005-bopenalex-snapshot
Neural network modelling and control strategies for a pH process
inferredcites →https://doi.org/10.1016/0959-1524(95)90348-iopenalex-snapshot
A very simple structure for neural network control of distillation
inferredcites →https://doi.org/10.1016/b978-0-12-480575-0.50008-3openalex-snapshot
Fault Detection and Diagnosis Using Artificial Neural Networks1
inferredcites →https://doi.org/10.1016/c2009-0-21189-5openalex-snapshot
Neural Networks in Bioprocessing and Chemical Engineering
inferredcites →https://doi.org/10.1016/s0005-1098(99)00092-8openalex-snapshot
Stable adaptive control with recurrent networks
inferredcites →https://doi.org/10.1016/s0009-2509(99)00179-7openalex-snapshot
Use of neural net computing for statistical and kinetic modelling and simulation of supercritical fluid extractors
inferredcites →https://doi.org/10.1016/s0016-0032(96)00059-2openalex-snapshot
Nonlinear identification and control of a heat exchanger: A neural network approach
inferredcites →https://doi.org/10.1016/s0019-0578(99)00025-7openalex-snapshot
Application of neural network control to distillation and an experimental comparison with other advanced controllers
inferredcites →https://doi.org/10.1016/s0019-0578(99)00031-2openalex-snapshot
A neural network strategy for end-point optimization of batch processes
inferredcites →https://doi.org/10.1016/s0019-0578(99)00032-4openalex-snapshot
Control of chemical processes using neural networks: implementation in a plant for xylose production
inferredcites →https://doi.org/10.1016/s0098-1354(96)00332-8openalex-snapshot
Application of artificial neural networks for crossflow microfiltration modelling: “black-box” and semi-physical approaches
inferredcites →https://doi.org/10.1016/s0098-1354(97)00184-1openalex-snapshot
Inferential Estimation of Polymer Quality Using Stacked Neural Networks
inferredcites →https://doi.org/10.1016/s0098-1354(97)00217-2openalex-snapshot
Adaptive and predictive control strategies for batch distillation: Development and experimental testing
inferredcites →https://doi.org/10.1016/s0098-1354(97)00218-4openalex-snapshot
Neuro-fuzzy modeling and control of a batch process involving simultaneous reaction and distillation
inferredcites →https://doi.org/10.1016/s0098-1354(97)00269-xopenalex-snapshot
Long-term prediction models based on mixed order locally recurrent neural networks
inferredcites →https://doi.org/10.1016/s0098-1354(98)00104-5openalex-snapshot
Intelligent modelling in the chemical process industry with neural networks: a case study
inferredcites →https://doi.org/10.1016/s0098-1354(98)00157-4openalex-snapshot
Strategies for modeling and control of nonlinear chemical processes using neural networks
inferredcites →https://doi.org/10.1016/s0098-1354(98)00174-4openalex-snapshot
A hybrid neural network-first principles approach to batch unit optimisation
inferredcites →https://doi.org/10.1016/s0098-1354(98)00178-1openalex-snapshot
Simulation of an absorption column performance using feed-forward neural networks in nitric acid production
inferredcites →https://doi.org/10.1016/s0098-1354(98)00191-4openalex-snapshot
Identification of distributed parameter systems: A neural net based approach
inferredcites →https://doi.org/10.1016/s0098-1354(98)00194-xopenalex-snapshot
Waste analysis and minimization in batch and semibatch reactor operation through dynamic simulation and neural networks
inferredcites →https://doi.org/10.1016/s0098-1354(98)00195-1openalex-snapshot
Modeling and optimization of pulp and paper processes using neural networks
inferredcites →https://doi.org/10.1016/s0098-1354(98)00223-3openalex-snapshot
Neural networks for the identification of the aluminium electrolysis process
inferredcites →https://doi.org/10.1016/s0098-1354(99)00274-4openalex-snapshot
Neural networks for the prediction of the state of Zymomonas mobilis CP4 batch fermentations
inferredcites →https://doi.org/10.1016/s0893-6080(96)00097-4openalex-snapshot
Closed Loop Nonlinear Process Identification Using Internally Recurrent Nets
inferredcites →https://doi.org/10.1016/s0893-6080(98)00087-2openalex-snapshot
A modified back-propagation method to avoid false local minima
inferredcites →https://doi.org/10.1016/s1474-6670(17)44942-1openalex-snapshot
Adaptive Control of Nonlinear Chemical Processes Using Neural Networks
inferredcites →https://doi.org/10.1016/s1474-6670(17)44943-3openalex-snapshot
A Semi-Empirical and a Neural Network Model of a Batch Plant Dynamics for Flexible Recipes Control
inferredcites →https://doi.org/10.1016/s1474-6670(17)47024-8openalex-snapshot
Identification of a Pilot Plant Reactive Distillation Process using RBF Networks
inferredcites →https://doi.org/10.1016/s1474-6670(17)48129-8openalex-snapshot
System Identification of an Adsorption Process Using Neural Networks
inferredcites →https://doi.org/10.1016/s1474-6670(17)50241-4openalex-snapshot
Use of Artificial Neural Networks to Monitor Faults and for Troubleshooting in the Process Industries
inferredcites →https://doi.org/10.1016/s1474-6670(17)50715-6openalex-snapshot
Overtraining, Regularization, and Searching for Minimum in Neural Networks
inferredcites →https://doi.org/10.1016/s1474-6670(17)50971-4openalex-snapshot
State Prediction for Chemical Reactors Using Feedback Neural Networks
inferredcites →https://doi.org/10.1016/s1474-6670(17)50999-4openalex-snapshot
Predictive Control of Distillation Columns Using Dynamic Neural Networks
inferredcites →https://doi.org/10.1016/s1474-6670(17)51197-0openalex-snapshot
Fault Classification with the AID of Artificial Neural Networks
inferredcites →https://doi.org/10.1016/s1474-6670(17)53353-4openalex-snapshot
Use of Neural Nets for Modeling of Chemical Process Systems
inferredcites →https://doi.org/10.1016/s1474-6670(17)53362-5openalex-snapshot
A Neural Net to Learn the Design of Distillation Controls
inferredcites →https://doi.org/10.1016/s1474-6670(17)58652-8openalex-snapshot
Estimation of Measurement Biases Using Recurrent Neural Networks and the Extended Kalman Filter
inferredcites →https://doi.org/10.1016/s1474-6670(17)58672-3openalex-snapshot
CMAC-Based Learning Control for a Batch Reactor
inferredcites →https://doi.org/10.1016/s1474-6670(17)58771-6openalex-snapshot
Modeling of Activated Sludge Wastewater Treatment Processes Using Integrated Neural Networks and a First Principle Model
inferredcites →https://doi.org/10.1021/i200022a024openalex-snapshot
Fault detection and diagnosis via parameter estimation in lumped dynamic systems
inferredcites →https://doi.org/10.1021/i200034a037openalex-snapshot
Comparison of two approaches to on-line parameter and state estimation of nonlinear systems
inferredcites →https://doi.org/10.1021/ie00021a019openalex-snapshot
Predictive control of quality in a batch manufacturing process using artificial neural network models
inferredcites →https://doi.org/10.1021/ie00024a010openalex-snapshot
Data rectification and gross error detection in a steady state process via artificial neural networks
inferredcites →https://doi.org/10.1021/ie00030a011openalex-snapshot
Pattern Recognition Based Adaptive Control of Two-Input/Two-Output Systems Using ART2-A Neural Networks
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Prediction of Solvent Activity in Polymer Systems with Neural Networks
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Identification of Nonlinear Dynamic Processes with Unknown and Variable Dead Time Using an Internal Recurrent Neural Network
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Nonlinear Dynamic Artificial Neural Network Modeling Using an Information Theory Based Experimental Design Approach
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Software Sensor Design Using Bayesian Automatic Classification and Back-Propagation Neural Networks
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Design of a Combined Mixing Rule for the Prediction of Vapor−Liquid Equilibria Using Neural Networks
inferredcites →https://doi.org/10.1021/ie980630yopenalex-snapshot
HETP and Pressure Drop Prediction for Structured Packing Distillation Columns Using a Neural Network Model
inferredcites →https://doi.org/10.1021/ie990312eopenalex-snapshot
Generalized Multivariable Dynamic Artificial Neural Network Modeling for Chemical Processes
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Optimal design of aquifer cleanup systems under uncertainty using a neural network and a genetic algorithm
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Fuzzy neural networks for nonlinear systems modelling
inferredcites →https://doi.org/10.1049/ip-d.1991.0036openalex-snapshot
Artificial neural networks in process engineering
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Introduction to the Theory of Neural Computation
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Correlation based model validity tests for non-linear models
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Non-linear systems identification using radial basis functions
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Feedforward Neural Network Methodology
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Statistics and Neural Networks
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NEURAL NETWORK FOR CLASSIFYING FLOW IN A TANK
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NEURAL NETS SPEED FLOW CALCULATION
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Statistics and Neural Networks
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Robust radial basis function neural networks
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Backpropagation through time: what it does and how to do it
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Constructing a reliable neural network model for a plasma etching process using limited experimental data
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Predictive control of a bench-scale chemical reactor based on neural-network models
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Application of Neural Networks in Bioprocess State Estimation
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On-line sensor validation of single sensors using artificial neural networks
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Identification of nonlinear processes with dead time by recurrent neural networks
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Nonlinear control of an oil well
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Artificial neural network feedforward/feedback control of a batch polymerization reactor
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Towards real time fault identification in plasma etching using neural networks
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Three neural network based, sensor systems for environmental monitoring
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Temporal sequence processing based on the biological reaction-diffusion process
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Dynamic data rectification using the extended Kalman filter and recurrent neural networks
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The tracking of changes in chemical processes using computer vision and self-organizing maps
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Utilising artificial neural network and repro-modelling in turbulent combustion
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Modeling of unsteady heat conduction field by using composite recurrent neural networks
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A neural architecture to predict pollution in industrial areas
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Online prediction of polymer product quality in an industrial reactor using recurrent neural networks
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Prediction of products quality parameters of a crude fractionation section of an oil refinery using neural networks
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The state estimation of the CSTR system based on a recurrent neural network trained by HGAs
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The model reference adaptive control based on the genetic algorithm
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Modeling liquid phase oxygenation process using neural network
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Incipient fault detection and diagnosis using artificial neural networks
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Application of feedforward and recurrent neural networks to chemical plant predictive modeling
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Application of feed-forward neural networks for system identification of a biochemical process
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Using recurrent multilayer neural network for simulating batch reactors
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Data rectification using recurrent (Elman) neural networks
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A policy- and experience- driven neural network (PENN) and its application to SISO and MIMO process control
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Evaluation of the thermodynamic models UNIQUAC and UNIFAC using artificial neural networks
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Neural net based model predictive control of a chaotic continuous solution polymerization reactor
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Flow rate measurement in air-water horizontal pipeline by neural networks
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A system identification perspective on neural nets
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Vision of neural networks and fuzzy logic for prediction and optimization of manufacturing processes
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Pruning Using Parameter and Neuronal Metrics
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What Size Net Gives Valid Generalization?
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Neural Networks and the Bias/Variance Dilemma
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Neural Network Modeling of Serum Protein Fractionation Using Gel Filtration Chromatography.
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Multi-Objective Optimization for Site Location Problems through Hybrid Genetic Algorithm with Neural Networks.
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Pattern Recognition of Microstructures using Neural Networks
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Development of Control Strategies via Artificial Neural Networks and Reinforcement Learning
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Fault Detection in Heat Exchangers
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Stable adaptive control with recurrent networks
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STRAIGHT LINE REGRESSION WHEN BOTH VARIABLES ARE SUBJECT TO ERROR
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Artificial Neural Networks
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Parallel Distributed Processing
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Multiscale Analysis for the Exploitation of Bioresources
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ML@ChemE: Past, Present, and Future of Machine Learning in Chemical Engineering
inferred← citeshttps://doi.org/10.1002/cctc.201200665openalex-snapshot
Knowledge Extraction from Catalysis of the Past: A Case of Selective CO Oxidation over Noble Metal Catalysts between 2000 and 2012
inferred← citeshttps://doi.org/10.1002/ceat.200800486openalex-snapshot
Fault Detection and Diagnosis in a Sour Gas Absorption Column Using Neural Networks
inferred← citeshttps://doi.org/10.1002/ceat.201000361openalex-snapshot
Artificial Neural Network for Modeling the Extraction of Aromatic Hydrocarbons from Lube Oil Cuts
inferred← citeshttps://doi.org/10.1002/ceat.201500186openalex-snapshot
Artificial Neural Network Modeling of Hydrodynamics of Liquid‐Solid Circulating Fluidized Beds
inferred← citeshttps://doi.org/10.1002/ceat.202100170openalex-snapshot
Minimum Fluidization Velocities of Binary Solid Mixtures: Empirical Correlation and Genetic Algorithm‐Artificial Neural Network Modeling
inferred← citeshttps://doi.org/10.1002/cite.201400142openalex-snapshot
Anforderungen der zukunftsorientierten Spezialchemie an die angewandte Reaktionstechnik
inferred← citeshttps://doi.org/10.1002/cjce.21838openalex-snapshot
Pressure drop in tapered bubble columns using non‐Newtonian pseudoplastic liquid—experimental and ANN prediction
inferred← citeshttps://doi.org/10.1002/cjce.24477openalex-snapshot
Hybrid smart model to determine concentration of acidic gases in absorption tower of sweetening process
inferred← citeshttps://doi.org/10.1002/cjce.5450800415openalex-snapshot
Dynamic Process Modelling using a PCA‐based Output Integrated Recurrent Neural Network
inferred← citeshttps://doi.org/10.1002/htj.21970openalex-snapshot
Genetic algorithm‐assisted artificial neural network for retrieval of a parameter in a third grade fluid flow through two parallel and heated plates
inferred← citeshttps://doi.org/10.1007/978-3-030-65283-8_16openalex-snapshot
Neural Network Modeling of the Kinetic Characteristics of Polymer Composites Curing Process
inferred← citeshttps://doi.org/10.1007/978-3-030-95459-8_15openalex-snapshot
Embedded Neural Networks for Robot Autonomy
inferred← citeshttps://doi.org/10.1007/978-3-031-10766-5_28openalex-snapshot
A Comparative Study of Prediction of Gas Hold up Using ANN
inferred← citeshttps://doi.org/10.1007/978-3-032-26858-7_19openalex-snapshot
AI-Driven Circular Economy: Optimizing Industrial Use and Recovery of Trace Elements and Heavy Metals
inferred← citeshttps://doi.org/10.1007/978-3-319-19066-2_38openalex-snapshot
Evaluation of the Rate Constants of Reactions of Phenyl Radicals with Hydrocarbons with the Use of Artificial Neural Network
inferred← citeshttps://doi.org/10.1007/978-3-319-99987-6_15openalex-snapshot
Genetic Selection of Training Sets for (Not Only) Artificial Neural Networks
inferred← citeshttps://doi.org/10.1007/978-3-642-00248-9_8openalex-snapshot
Modeling of Dilute and Dense Phase in Generalized Fluidization
inferred← citeshttps://doi.org/10.1007/978-81-322-2250-7_82openalex-snapshot
Flow Regime Prediction Using Artificial Neural Networks for Air-Water Flow Through 1–5 mm Tubes in Horizontal Plane
inferred← citeshttps://doi.org/10.1007/978-981-10-6463-0_26openalex-snapshot
Artificial Neural Network for Anomalies Detection in Distillation Column
inferred← citeshttps://doi.org/10.1007/978-981-15-0474-7_40openalex-snapshot
Nonlinear Observer Based Fault Diagnosis for an Innovative Intensified Heat-Exchanger/Reactor
inferred← citeshttps://doi.org/10.1007/978-981-33-4862-2_21openalex-snapshot
Predicting Material Stability Using Machine Learning
inferred← citeshttps://doi.org/10.1007/978-981-97-7296-4_10openalex-snapshot
Artificial Neural Network Code for Friction Factor Prediction in Smooth Pipe Bends
inferred← citeshttps://doi.org/10.1007/bf02697143openalex-snapshot
Adaptive modeling and classification of the secondary settling tank
inferred← citeshttps://doi.org/10.1007/bf02698284openalex-snapshot
Process system engineering in wastewater treatment process
inferred← citeshttps://doi.org/10.1007/bf02698304openalex-snapshot
Preparations of silica slurry for wafer polishing via controlled growth of commercial silica seeds
inferred← citeshttps://doi.org/10.1007/bf02705492openalex-snapshot
Experimental and modeling study on CO2 absorption in a cyclone scrubber by phenomenological model and neural networks
inferred← citeshttps://doi.org/10.1007/bf02705543openalex-snapshot
Steady-state modeling of coal boilers
inferred← citeshttps://doi.org/10.1007/bf02705598openalex-snapshot
Superstructure of yOTs-the network-based chemical process operator training system for multiple trainees
inferred← citeshttps://doi.org/10.1007/bf02705659openalex-snapshot
Dynamic neural network modeling for hydrochloric acid recovery process
inferred← citeshttps://doi.org/10.1007/bf02706377openalex-snapshot
A method of model validation for chaotic chemical reaction systems based on neural network
inferred← citeshttps://doi.org/10.1007/s00449-013-1073-5openalex-snapshot
Neural network modeling of the light profile in a novel photobioreactor
inferred← citeshttps://doi.org/10.1007/s00477-007-0123-4openalex-snapshot
A neural network approach for the real-time detection of faults
inferred← citeshttps://doi.org/10.1007/s00521-022-07851-9openalex-snapshot
Heuristic optimisation of multi-task dynamic architecture neural network (DAN2)
inferred← citeshttps://doi.org/10.1007/s00521-024-09556-7openalex-snapshot
Time-varying neural networks for multi-input multi-output systems: a reactive batch distillation modeling case study
inferred← citeshttps://doi.org/10.1007/s10570-022-04631-5openalex-snapshot
Artificial neural network for aspect ratio prediction of lignocellulosic micro/nanofibers
inferred← citeshttps://doi.org/10.1007/s11063-020-10335-3openalex-snapshot
Stochastic One-Step Training for Feedforward Artificial Neural Networks
inferred← citeshttps://doi.org/10.1007/s11270-021-05070-xopenalex-snapshot
Adsorptive Elimination of Cu(II) from Aqueous Solution by Chitosan-nanoSiO2 Nanocomposite—Adsorption Study, MLR, and GA Modeling
inferred← citeshttps://doi.org/10.1007/s11814-008-0155-6openalex-snapshot
Data reconciliation: Development of an object-oriented software tool
inferred← citeshttps://doi.org/10.1007/s11814-010-0512-0openalex-snapshot
Viscosity of ionic liquids using the concept of mass connectivity and artificial neural networks
inferred← citeshttps://doi.org/10.1007/s11814-011-0117-2openalex-snapshot
Dynamic simulation based fault detection and diagnosis for distillation column
inferred← citeshttps://doi.org/10.1007/s11814-011-0235-xopenalex-snapshot
PRSV equation of state parameter modeling through artificial neural network and adaptive network-based fuzzy inference system
inferred← citeshttps://doi.org/10.1007/s11814-011-0250-yopenalex-snapshot
Modeling the oxidative coupling of methane using artificial neural network and optimizing of its operational conditions using genetic algorithm
inferred← citeshttps://doi.org/10.1007/s11814-016-0304-2openalex-snapshot
Optimization of supercritical extraction of galegine from Galega officinalis L.: Neural network modeling and experimental optimization via response surface methodology
inferred← citeshttps://doi.org/10.1007/s11814-023-1518-8openalex-snapshot
Automatic anomaly detection in engineering diagrams using machine learning
inferred← citeshttps://doi.org/10.1007/s11814-024-00150-0openalex-snapshot
Trends of Chemical Engineering Applications in the Last Three Decades: A Scientometric and Retrospective Review
inferred← citeshttps://doi.org/10.1007/s11814-024-00246-7openalex-snapshot
Current Progress in the Application of Artificial Intelligence for Nuclear Power Plant Operation
inferred← citeshttps://doi.org/10.1007/s12555-024-0990-1openalex-snapshot
Reinforcement Learning for Process Control: Review and Benchmark Problems
inferred← citeshttps://doi.org/10.1007/s13201-018-0790-yopenalex-snapshot
Application of RSM and ANN for optimization and modeling of biosorption of chromium(VI) using cyanobacterial biomass
inferred← citeshttps://doi.org/10.1007/s13369-014-1556-yopenalex-snapshot
Azo Dye DB71 Degradation Using Ultrasonic-Assisted Fenton Process: Modeling and Process Optimization
inferred← citeshttps://doi.org/10.1007/s13738-022-02703-8openalex-snapshot
Checking the performance of feed-forward and cascade artificial neural networks for modeling the surface tension of binary hydrocarbon mixtures
inferred← citeshttps://doi.org/10.1007/s41062-023-01150-5openalex-snapshot
A review of soft computing techniques in predicting the compressive strength of concrete and the future scope
inferred← citeshttps://doi.org/10.1016/b978-0-08-101095-2.00011-4openalex-snapshot
Control and Optimization of Batch Chemical Processes
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Hybrid Mechanistic Data-Driven Modeling for the Deterministic Global Optimization of a Transcritical Organic Rankine Cycle
inferred← citeshttps://doi.org/10.1016/b978-0-12-824463-0.00006-9openalex-snapshot
Modeling Undefined Complexities of Wastewater Treatment Processes With Artificial Neural Network
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Development of a Neural Network-based Renewable Energy Forecasting Framework for Process Industries
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Data-driven Modeling and Optimization of Complex Chemical Processes Using a Novel HDMR Methodology
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Analysis of selective CO oxidation over promoted Pt/Al2O3 catalysts using modular neural networks: Combining preparation and operational variables
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Combined approach using mathematical modelling and artificial neural network for chemical industries: Steam methane reformer
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Dynamic-model-based artificial neural network for H2 recovery and CO2 capture from hydrogen tail gas
inferred← citeshttps://doi.org/10.1016/j.applthermaleng.2016.09.159openalex-snapshot
Modelling of dust removal in rotating packed bed using artificial neural networks (ANN)
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Artificial neural network modeling of biosorption process using agricultural wastes in a rotating packed bed
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Simplifying the interpretation of ToF-SIMS spectra and images using careful application of multivariate analysis
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Random vector functional link network: Recent developments, applications, and future directions
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Artificial neural network approach towards the separation of ethylparaben and diclofenac using pseudo-emulsion hollow fiber strip dispersion technique
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A unified framework for the mathematical modelling, predictive analysis, and optimization of reaction systems using computational fluid dynamics, deep neural network and genetic algorithm: A case of butadiene synthesis
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Speeding up turbulent reactive flow simulation via a deep artificial neural network: A methodology study
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Gas-liquid flow in small channels: Artificial neural network classifiers for flow regime prediction
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Non-spherical solid-non-Newtonian liquid fluidization and ANN modelling: Minimum fluidization velocity
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Supervised machine learning for prediction of zirconocene-catalyzed α-olefin polymerization
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Performance analysis and artificial intelligence modeling for enhanced hydrogen production by catalytic bio-alcohol reforming in a membrane-assisted reactor
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Intensification of reaction-extraction coupling in a rotor-stator submerged rotating packed bed reactor: Biphasic fructose dehydration to 5-hydroxymethylfurfural
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Synchronization results for uncertain complex-valued neural networks under delay-dependent flexible impulsive control
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Data mining for pesticide decontamination using heterogeneous photocatalytic processes
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Modeling preferential CO oxidation over promoted Au/Al2O3 catalysts using decision trees and modular neural networks
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Modelling of adsorption in rotating packed bed using artificial neural networks (ANN)
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Architectures for neural networks as surrogates for dynamic systems in chemical engineering
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A novel nested loop optimization problem based on deep neural networks and feasible operation regions definition for simultaneous material screening and process optimization
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Neural network-based model predictive control for thin-film chemical deposition of quantum dots using data from a multiscale simulation
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Predictive analysis of gas hold-up in bubble column using machine learning methods
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A framework for model maintenance using kernel-based forward propagating neural networks
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Operational optimization of crude oil distillation systems using artificial neural networks
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Optimization of naphtha purchase price using a price prediction model
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Large scale optimization of a sour water stripping plant using surrogate models
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Deterministic global process optimization: Accurate (single-species) properties via artificial neural networks
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Artificial Neural Network control of thermoelectrically-cooled microfluidics using computer vision based on IR thermography
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Integrating deep learning models and multiparametric programming
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Process safety consequence modeling using artificial neural networks for approximating heat exchanger overpressure severity
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Data augmentation driven by optimization for membrane separation process synthesis
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Online parameter estimation and model maintenance using parameter-aware physics-informed neural network
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Deep neural networks in chemical engineering classrooms to accurately model adsorption equilibrium data
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Combined mathematical and artificial intelligence modeling of catalytic bio-methanol conversion to dimethyl ether
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Renewable ammonia synthesis via experiments and optimization using periodic operation and machine learning integrated approaches
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Neural modeling helps the BOS process to achieve aimed end-point conditions in liquid steel
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State estimation and inferential control for a reactive batch distillation column
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A data-driven tracking control framework using physics-informed neural networks and deep reinforcement learning for dynamical systems
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Modeling of oily sludge composting process by using artificial neural networks and differential evolution: Prediction of removal of petroleum hydrocarbons and organic carbon
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Investigating vapor–liquid equilibria of binary mixtures containing supercritical or near-critical carbon dioxide and a cyclic compound using cascade neural network
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Estimation of CO2 solubility in ionic liquids using connectionist tools based on thermodynamic and structural characteristics
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A simulation study on NOx reduction efficiency in SCR catalysts utilizing a modern C3-CNN algorithm
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Inverse design of operational parameters for iron-rich phase separation from solid waste melts in induction furnace through transport phenomena analysis and multi-objective optimization
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The Integration of Explicit MPC and ReLU based Neural Networks
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In-situ FT-IR quantitative analysis of amine concentrations and CO2 loading amount in solvent mixtures for CO2 capture
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Investigation of water gas-shift activity of Pt–MOx–CeO2/Al2O3 (M = K, Ni, Co) using modular artificial neural networks
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Sensitivity analysis and artificial neural network-based optimization for low-carbon H2 production via a sorption-enhanced steam methane reforming (SESMR) process integrated with separation process
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Application of artificial neural networks for Process Analytical Technology-based dissolution testing
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A survey towards an integration of big data analytics to big insights for value-creation
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Multiple target data-driven models to enable sustainable process manufacturing: An industrial bioprocess case study
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Predicting overall mass transfer coefficients of CO2 capture into monoethanolamine in spray columns with hybrid machine learning
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A comparative study of multi-objective optimization with ANN-based VPSA model for CO2 capture from dry flue gas
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Cloud manufacturing as a sustainable process manufacturing route
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Rigorous modeling of CO2 equilibrium absorption in MEA, DEA, and TEA aqueous solutions
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Reliability evaluation method for pipes buried in fault areas based on the probabilistic fault displacement hazard analysis
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Co-gasification of rice husk and plastic in the presence of CaO using a novel ANN model-incorporated Aspen plus simulation
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Neural network based model predictive control for a steel pickling process
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Parametric study and modeling of cross-flow heat exchanger fouling in phosphoric acid concentration plant using artificial neural network
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Application of a radial basis function neural network to estimate pressure gradient in water–oil pipelines
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Investigating and modeling the cleaning-in-place process for retrieving the membrane permeate flux: Case study of hydrophilic polyethersulfone (PES)
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Corrosion and mechanical properties of nanostructure electrolytic Co-W and Fe-Co-W alloys
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Artificial neural network modeling techniques applied to the hydrodesulfurization process
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Prediction of pore properties of hierarchical porous silica templated on natural rubber
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Prediction of terminal velocity of solid spheres falling through Newtonian and non-Newtonian pseudoplastic power law fluid using artificial neural network
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Estimation of the saturation pressure of pure ionic liquids using MLP artificial neural networks and the revised isofugacity criterion
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Prediction of pressure drop using artificial neural network for non-Newtonian liquid flow through piping components
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Prediction of Frictional Pressure Drop Using Artificial Neural Network for Air-water Flow through U-bends
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A sequential probability ratio test (SPRT) to detect changes and process safety monitoring
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Facile estimation of viscosity of natural amino acid salt solutions: Empirical models vs artificial intelligence
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Detecting Changes in a Distillation Column by Using a Sequential Probability Ratio Test
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Prediction of solubility of solid compounds in supercritical CO2 using a connectionist smart technique
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ANN based modelling of hydrodynamic cavitation processes: Biomass pre-treatment and wastewater treatment
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Calculation of the Pitot tube correction factor for Newtonian and non-Newtonian fluids
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Nonlinear regression using RBFN with linear submodels
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Neural network applications for detecting process faults in packed towers
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Joint analysis of process and operator performance in chemical process operational safety
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Artificial neural network modeling of a multiphase photodegradation system
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Facile and Accurate Calculation of the Density of Amino Acid Salt Solutions: A Simple and General Correlation vs Artificial Neural Networks
inferred← citeshttps://doi.org/10.1021/acs.iecr.0c00729openalex-snapshot
Dynamic Surrogate Modeling for Multistep-ahead Prediction of Multivariate Nonlinear Chemical Processes
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Linking Models and Experiments
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Perspectives on the Essential Role of First-Principles Modeling in the Age of AI
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Real-Time Adaptive Machine-Learning-Based Predictive Control of Nonlinear Processes
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Machine Learning Meets with Metal Organic Frameworks for Gas Storage and Separation
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Modeling of Hydrodynamic Cavitation Reactors: Reflections on Present Status and Path Forward
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Machine Learning for Catalytic Reaction Systems: A Framework for Complex Chemical Processes
inferred← citeshttps://doi.org/10.1021/ie020270lopenalex-snapshot
Modeling of Multistage Air-Compression Systems in Chemical Processes
inferred← citeshttps://doi.org/10.1021/ie030585gopenalex-snapshot
Artificial Neural Network Estimator Design for the Inferential Model Predictive Control of an Industrial Distillation Column
inferred← citeshttps://doi.org/10.1021/ie1007739openalex-snapshot
Prediction of Pressure Drop Using Artificial Neural Network for Gas Non-Newtonian Liquid Flow through Piping Components
inferred← citeshttps://doi.org/10.1021/ie2017543openalex-snapshot
Hybrid Compressor Model for Optimal Operation of Compressed Dry Air System in LCD Production Industry
inferred← citeshttps://doi.org/10.1021/ie403507popenalex-snapshot
Simulation-Based Optimization Methodology for Offshore Natural Gas Liquefaction Process Design
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Optimization of Heat-Integrated Crude Oil Distillation Systems. Part I: The Distillation Model
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Accounts of Experiences in the Application of Artificial Neural Networks in Chemical Engineering
inferred← citeshttps://doi.org/10.1021/jf8005239openalex-snapshot
Solving the Spectroscopy Interference Effects of β-Carotene and Lycopene by Neural Networks
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Neural Network Analysis of Spectroscopic Data of Lycopene and β-Carotene Content in Food Samples Compared to HPLC-UV-Vis
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Kinase inhibitor screening using artificial neural networks and engineered cardiac biowires
inferred← citeshttps://doi.org/10.1039/c6ra10897kopenalex-snapshot
Experimental determination and model correlation for the solubilities of trialkyl phosphates in supercritical carbon dioxide
inferred← citeshttps://doi.org/10.1063/5.0206840openalex-snapshot
How neural networks work: Unraveling the mystery of randomized neural networks for functions and chaotic dynamical systems
inferred← citeshttps://doi.org/10.1063/5.0287064openalex-snapshot
Neural network based prediction analysis of friction factor in smooth pipe bends
inferred← citeshttps://doi.org/10.1073/pnas.1909985116openalex-snapshot
Optimizing organic electrosynthesis through controlled voltage dosing and artificial intelligence
inferred← citeshttps://doi.org/10.1080/00084433.2023.2215013openalex-snapshot
Spectroscopic characterisation of feedstock for copper smelters by machine-learning
inferred← citeshttps://doi.org/10.1080/00986445.2013.766603openalex-snapshot
PREDICTION OF HORIZONTAL OIL-WATER FLOW PRESSURE GRADIENT USING ARTIFICIAL INTELLIGENCE TECHNIQUES
inferred← citeshttps://doi.org/10.1080/00986445.2016.1194273openalex-snapshot
Surface Tension Estimation of Binary Mixtures of Organic Compounds Using Artificial Neural Networks
inferred← citeshttps://doi.org/10.1080/00986445.2016.1206892openalex-snapshot
Artificial Neural Network Modeling of Mixing Efficiency in a Split-Cylinder Gas-Lift Bioreactor for Yarrowia lipolytica Suspensions
inferred← citeshttps://doi.org/10.1080/00986445.2018.1430574openalex-snapshot
Soft-sensor models to estimate the efficiency of H2S removal from an oil refinery stream of nonphenolic sour water
inferred← citeshttps://doi.org/10.1080/00986445.2018.1505614openalex-snapshot
Thermal performance prediction of wickless heat pipe with Al2O3/water nanofluid using artificial neural network
inferred← citeshttps://doi.org/10.1080/01496395.2012.665975openalex-snapshot
Using Artificial Neural Network to Predict the Pressure Drop in a Rotating Packed Bed
inferred← citeshttps://doi.org/10.1080/01496395.2015.1024259openalex-snapshot
Development of Reliable Models for Determination of Required Monoethanolamine (MEA) Circulation Rate in Amine Plants
inferred← citeshttps://doi.org/10.1080/01496395.2020.1828460openalex-snapshot
Insight into the Estimation of Equilibrium CO2 Absorption by Deep Eutectic Solvents using Computational Approaches
inferred← citeshttps://doi.org/10.1080/01614940.2020.1770402openalex-snapshot
Recent advances in knowledge discovery for heterogeneous catalysis using machine learning
inferred← citeshttps://doi.org/10.1080/01932691.2017.1391702openalex-snapshot
Prediction of characteristic properties of crude oil blending with ANN
inferred← citeshttps://doi.org/10.1080/02726351.2023.2219983openalex-snapshot
Terminal settling velocity of the binary solid mixture in the non-Newtonian pseudoplastic liquid system
inferred← citeshttps://doi.org/10.1080/03602559.2011.651243openalex-snapshot
Effect of Different Parameters on WEPS Production and Thermal Behavior Prediction Using Artificial Neural Network (ANN)
inferred← citeshttps://doi.org/10.1080/07373937.2012.718308openalex-snapshot
On the Use of Artificial Neural Networks to Monitor a Pharmaceutical Freeze-Drying Process
inferred← citeshttps://doi.org/10.1080/09593330.2012.750381openalex-snapshot
Modelling and optimization of Mn/activate carbon nanocatalysts for NO reduction: comparison of RSM and ANN techniques
inferred← citeshttps://doi.org/10.1080/10934529.2016.1170438openalex-snapshot
Degradation of aqueous methylene blue using an external loop airlift sonophotoreactor: Statistical analysis and optimization
inferred← citeshttps://doi.org/10.1080/15567036.2018.1548507openalex-snapshot
Prediction of jatropha-algae biodiesel blend oil yield with the application of artificial neural networks technique
inferred← citeshttps://doi.org/10.1080/19443994.2013.797545openalex-snapshot
Electrocoagulation efficiency and energy consumption probing by artificial intelligent approaches
inferred← citeshttps://doi.org/10.1080/19443994.2013.821040openalex-snapshot
Synthesis of ZnO nano-sono-catalyst for degradation of reactive dye focusing on energy consumption: operational parameters influence, modeling, and optimization
inferred← citeshttps://doi.org/10.1080/19443994.2014.937756openalex-snapshot
Fast artificial neural network (FANN) modeling of Cd(II) ions removal by valonia resin
inferred← citeshttps://doi.org/10.1109/ascc.2013.6606356openalex-snapshot
Optimized real-time soft analyzer for chemical process using artificial intelligence
inferred← citeshttps://doi.org/10.1109/cica.2009.4982788openalex-snapshot
Design of online soft sensors based on combined adaptive PCA and RBF neural networks
inferred← citeshttps://doi.org/10.1109/ijcnn.2006.1716225openalex-snapshot
Design of State Estimators for the Inferential Control of an Industrial Distillation Column
inferred← citeshttps://doi.org/10.1109/sbrn.2002.1181426openalex-snapshot
Application of feedforward neural networks for soft sensors in the sugar industry
inferred← citeshttps://doi.org/10.1111/jfpe.14230openalex-snapshot
Machine‐learning predictions of caffeine co‐crystal formation accompanying experimental and molecular validations
inferred← citeshttps://doi.org/10.1117/12.2218728openalex-snapshot
Neural network modeling and model predictive control of ionic electroactive polymer actuators
inferred← citeshttps://doi.org/10.1134/s0040579519020027openalex-snapshot
A General Hybrid GMDH–PNN Model to Predict Thermal Conductivity for Different Groups of Nanofluids
inferred← citeshttps://doi.org/10.1134/s1070363219070144openalex-snapshot
Artificial Neural Network and Multiple Linear Regression for Prediction and Classification of Sustainability of Sodium and Potassium Coronates
inferred← citeshttps://doi.org/10.11606/d.76.2020.tde-06052020-104650openalex-snapshot
Espectroscopia Raman e redes neurais artificiais na identificação de minerais dos grupos do pirocloro e da microlita
inferred← citeshttps://doi.org/10.1162/089976699300016548openalex-snapshot
Pruning Using Parameter and Neuronal Metrics
inferred← citeshttps://doi.org/10.1177/0095244315618700openalex-snapshot
Effect of various material parameters on barrier properties of high-density polyethylene/polyamide 6/clay nanocomposites
inferred← citeshttps://doi.org/10.1179/174328107x203796openalex-snapshot
Reviving traditional blast furnace models with new mathematical approach
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