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Review of Anaerobic Digestion Modeling and Optimization Using Nature-Inspired Techniques
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Search and Optimization by Metaheuristics: Techniques and Algorithms Inspired by Nature
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Wastewater Treatment Energy Recovery Potential For Adaptation To Global Change: An Integrated Assessment
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Stochastic modeling applications for the prediction of COD removal efficiency of UASB reactors treating diluted real cotton textile wastewater
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Artificial Neural Network Modeling for Predicting Organic Matter in a Full-Scale Up-Flow Anaerobic Sludge Blanket (UASB) Reactor
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Mathematical modelling of anaerobic digestion processes: applications and future needs
inferredcites →https://doi.org/10.1007/s12559-015-9370-8openalex-snapshot
Nature Inspired Computing: An Overview and Some Future Directions
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An Artificial Neural Network and Genetic Algorithm Optimized Model for Biogas Production from Co-digestion of Seed Cake of Karanja and Cattle Dung
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Artificial intelligence models for predicting the performance of biological wastewater treatment plant in the removal of Kjeldahl Nitrogen from wastewater
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Estimation of kinetic parameters of an anaerobic digestion model using particle swarm optimization
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inferredcites →https://doi.org/10.1016/j.biortech.2015.08.017openalex-snapshot
An integrated prediction and optimization model of biogas production system at a wastewater treatment facility
inferredcites →https://doi.org/10.1016/j.biortech.2016.03.046openalex-snapshot
Artificial neural network based modeling to evaluate methane yield from biogas in a laboratory-scale anaerobic bioreactor
inferredcites →https://doi.org/10.1016/j.biortech.2017.03.101openalex-snapshot
A systematic methodology to extend the applicability of a bioconversion model for the simulation of various co-digestion scenarios
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Artificial neural network prediction of the biogas flow rate optimised with an ant colony algorithm
inferredcites →https://doi.org/10.1016/j.cej.2008.03.008openalex-snapshot
Prediction of effluent quality of an anaerobic treatment plant under unsteady state through ANFIS modeling with on-line input variables
inferredcites →https://doi.org/10.1016/j.ejor.2006.06.046openalex-snapshot
Ant colony optimization for continuous domains
inferredcites →https://doi.org/10.1016/j.envsoft.2004.09.006openalex-snapshot
Prediction of trace compounds in biogas from anaerobic digestion using the MATLAB Neural Network Toolbox
inferredcites →https://doi.org/10.1016/j.gee.2016.05.001openalex-snapshot
Multi-objective optimization of biomass to biomethane system
inferredcites →https://doi.org/10.1016/j.jhazmat.2007.01.098openalex-snapshot
Application of polyimide membranes for biogas purification and enrichment
inferredcites →https://doi.org/10.1016/j.pecs.2008.06.002openalex-snapshot
Principles and potential of the anaerobic digestion of waste-activated sludge
inferredcites →https://doi.org/10.1016/j.pecs.2013.03.003openalex-snapshot
Mathematical modelling of anaerobic digestion of biomass and waste: Power and limitations
inferredcites →https://doi.org/10.1016/j.plrev.2005.10.001openalex-snapshot
Ant colony optimization: Introduction and recent trends
inferredcites →https://doi.org/10.1016/j.renene.2005.09.029openalex-snapshot
Anaerobic co-digestion of primary sludge and the fruit and vegetable fraction of the municipal solid wastes
inferredcites →https://doi.org/10.1016/j.rser.2010.12.008openalex-snapshot
Optimization methods applied to renewable and sustainable energy: A review
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Co-digestion, pretreatment and digester design for enhanced methanogenesis
inferredcites →https://doi.org/10.1016/j.rser.2015.11.093openalex-snapshot
The use of neural modelling to estimate the methane production from slurry fermentation processes
inferredcites →https://doi.org/10.1016/j.rser.2016.11.184openalex-snapshot
Anaerobic co-digestion process for biogas production: Progress, challenges and perspectives
inferredcites →https://doi.org/10.1016/j.swevo.2011.06.003openalex-snapshot
Clustering using firefly algorithm: Performance study
inferredcites →https://doi.org/10.1016/j.wasman.2012.10.018openalex-snapshot
High-solids anaerobic co-digestion of sewage sludge and food waste in comparison with mono digestions: Stability and performance
inferredcites →https://doi.org/10.1016/j.wasman.2016.01.047openalex-snapshot
Optimal management of substrates in anaerobic co-digestion: An ant colony algorithm approach
inferredcites →https://doi.org/10.1016/j.watres.2011.08.059openalex-snapshot
Model selection, identification and validation in anaerobic digestion: A review
inferredcites →https://doi.org/10.1016/j.watres.2016.03.012openalex-snapshot
Modelling phosphorus (P), sulfur (S) and iron (Fe) interactions for dynamic simulations of anaerobic digestion processes
inferredcites →https://doi.org/10.1016/s0043-1354(00)00057-9openalex-snapshot
A fast predicting neural fuzzy model for high-rate anaerobic wastewater treatment systems
inferredcites →https://doi.org/10.1016/s0043-1354(01)00487-0openalex-snapshot
Advanced controlling of anaerobic digestion by means of hierarchical neural networks
inferredcites →https://doi.org/10.1080/15435075.2012.727116openalex-snapshot
Development of Ann-Based Models to Predict Biogas and Methane Productions in Anaerobic Treatment of Molasses Wastewater
inferredcites →https://doi.org/10.1089/ees.2012.0158openalex-snapshot
Evaluation of Anaerobic Biofilm Reactor Kinetic Parameters Using Ant Colony Optimization
inferredcites →https://doi.org/10.1109/ascc.2013.6606279openalex-snapshot
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inferredcites →https://doi.org/10.1109/setit.2012.6481891openalex-snapshot
Identification of bioprocesses using random search and Simulated Annealing algorithms
inferredcites →https://doi.org/10.1155/2015/931379openalex-snapshot
Stochastic Search Algorithms for Identification, Optimization, and Training of Artificial Neural Networks
inferredcites →https://doi.org/10.14311/nnw.2011.21.012openalex-snapshot
ARTIFICIAL INTELLIGENCE-BASED PREDICTION MODELS FOR ENVIRONMENTAL ENGINEERING
inferredcites →https://doi.org/10.1524/auto.2009.0809openalex-snapshot
Biogas Plant Control and Optimization Using Computational Intelligence MethodsBiogasanlagenregelung und -optimierung mit Computational Intelligence Methoden
inferredcites →https://doi.org/10.2166/wst.2002.0292openalex-snapshot
The IWA Anaerobic Digestion Model No 1 (ADM1)
inferredcites →https://doi.org/10.3182/20110828-6-it-1002.03208openalex-snapshot
Anaerobic digestion of biomass and waste: current trends in mathematical modeling
inferredcites →https://doi.org/10.4172/2324-9307.1000e101openalex-snapshot
Nature-Inspired Mateheuristic Algorithms: Success and New Challenges
inferredcites →https://doi.org/10.5281/zenodo.1061137openalex-snapshot
An Artificial Neural Network Based Model For Predicting H2 Production Rates In A Sucrose-Based Bioreactor System
inferredcites →https://doi.org/10.7551/mitpress/1290.001.0001openalex-snapshot
Ant Colony Optimization
inferredcites →https://doi.org/10.9734/bbj/2014/12755openalex-snapshot
Utilization of Genetic Algorithm to Optimize Biogas Production from Livestock Waste to Use in a CHP Plant in Agricultural Farms
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Advancing Bioenergy: In-situ and in-silico Approach To Enhance Anaerobic Digestion
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