On the public citation graph
Multifactor spatio-temporal correlation model based on a combination of convolutional neural network and long short-term memory neural network for wind speed forecasting
0 signed · 248 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-59497-3_175openalex-snapshot
The influence of the sigmoid function parameters on the speed of backpropagation learning
inferredcites →https://doi.org/10.1007/bf01386329openalex-snapshot
The norm of the Schur product operation
inferredcites →https://doi.org/10.1007/s00477-017-1435-7openalex-snapshot
Very short-term spatio-temporal wind power prediction using a censored Gaussian field
inferredcites →https://doi.org/10.1007/s40565-015-0171-6openalex-snapshot
Short-term wind power forecasting using hybrid method based on enhanced boosting algorithm
inferredcites →https://doi.org/10.1016/j.apenergy.2016.08.108openalex-snapshot
Deep belief network based deterministic and probabilistic wind speed forecasting approach
inferredcites →https://doi.org/10.1016/j.apenergy.2016.11.111openalex-snapshot
Deep learning based ensemble approach for probabilistic wind power forecasting
inferredcites →https://doi.org/10.1016/j.asoc.2017.05.031openalex-snapshot
Wind power prediction using deep neural network based meta regression and transfer learning
inferredcites →https://doi.org/10.1016/j.atmosenv.2016.10.046openalex-snapshot
Air quality early-warning system for cities in China
inferredcites →https://doi.org/10.1016/j.enconman.2015.05.065openalex-snapshot
Short-term wind power prediction based on LSSVM–GSA model
inferredcites →https://doi.org/10.1016/j.enconman.2016.02.013openalex-snapshot
Wind speed forecasting based on wavelet packet decomposition and artificial neural networks trained by crisscross optimization algorithm
inferredcites →https://doi.org/10.1016/j.enconman.2017.04.007openalex-snapshot
A compound structure of ELM based on feature selection and parameter optimization using hybrid backtracking search algorithm for wind speed forecasting
inferredcites →https://doi.org/10.1016/j.enconman.2017.07.065openalex-snapshot
Research and application of a novel hybrid forecasting system based on multi-objective optimization for wind speed forecasting
inferredcites →https://doi.org/10.1016/j.enconman.2018.01.010openalex-snapshot
Smart multi-step deep learning model for wind speed forecasting based on variational mode decomposition, singular spectrum analysis, LSTM network and ELM
inferredcites →https://doi.org/10.1016/j.enconman.2018.02.012openalex-snapshot
A novel hybrid forecasting system of wind speed based on a newly developed multi-objective sine cosine algorithm
inferredcites →https://doi.org/10.1016/j.enconman.2018.03.098openalex-snapshot
Wind speed forecasting using nonlinear-learning ensemble of deep learning time series prediction and extremal optimization
inferredcites →https://doi.org/10.1016/j.enconman.2018.04.021openalex-snapshot
Smart deep learning based wind speed prediction model using wavelet packet decomposition, convolutional neural network and convolutional long short term memory network
inferredcites →https://doi.org/10.1016/j.eswa.2017.04.053openalex-snapshot
Convolutional Neural Network approaches to granite tiles classification
inferredcites →https://doi.org/10.1016/j.eswa.2017.11.028openalex-snapshot
A new image classification method using CNN transfer learning and web data augmentation
inferredcites →https://doi.org/10.1016/j.neucom.2017.11.027openalex-snapshot
Input quality aware convolutional LSTM networks for virtual marine sensors
inferredcites →https://doi.org/10.1016/j.renene.2010.04.022openalex-snapshot
Wind speed forecasting in three different regions of Mexico, using a hybrid ARIMA–ANN model
inferredcites →https://doi.org/10.1016/j.renene.2016.09.069openalex-snapshot
Short-term wind power prediction based on spatial model
inferredcites →https://doi.org/10.1016/j.renene.2018.02.092openalex-snapshot
An experimental investigation of three new hybrid wind speed forecasting models using multi-decomposing strategy and ELM algorithm
inferredcites →https://doi.org/10.1016/j.rser.2015.12.223openalex-snapshot
Solar–wind hybrid renewable energy system: A review
inferredcites →https://doi.org/10.1016/j.trc.2015.03.014openalex-snapshot
Long short-term memory neural network for traffic speed prediction using remote microwave sensor data
inferredcites →https://doi.org/10.1016/s1364-0321(00)00004-6openalex-snapshot
Wind energy technology and current status: a review
inferredcites →https://doi.org/10.1049/iet-its.2016.0208openalex-snapshot
LSTM network: a deep learning approach for short‐term traffic forecast
inferredcites →https://doi.org/10.1080/00401706.2014.988291openalex-snapshot
Short-Term Wind Speed Forecast Using Measurements From Multiple Turbines in A Wind Farm
inferredcites →https://doi.org/10.1109/acc.2015.7172035openalex-snapshot
Low-dimensional models in spatio-temporal wind speed forecasting
inferredcites →https://doi.org/10.1109/tpami.2012.59openalex-snapshot
3D Convolutional Neural Networks for Human Action Recognition
inferredcites →https://doi.org/10.1109/tpwrs.2018.2794450openalex-snapshot
Correlation-Constrained and Sparsity-Controlled Vector Autoregressive Model for Spatio-Temporal Wind Power Forecasting
inferredcites →https://doi.org/10.1109/tste.2011.2163324openalex-snapshot
Application of Auto-Regressive Models to U.K. Wind Speed Data for Power System Impact Studies
inferredcites →https://doi.org/10.1109/tste.2015.2441747openalex-snapshot
Wind Power Forecasting Using Neural Network Ensembles With Feature Selection
inferredcites →https://doi.org/10.1198/073500102753410444openalex-snapshot
Comparing Predictive Accuracy
inferredcites →https://doi.org/10.3390/en10060812openalex-snapshot
Accurate Short-Term Power Forecasting of Wind Turbines: The Case of Jeju Island’s Wind Farm
inferredcites →https://doi.org/10.3390/en11040705openalex-snapshot
Wind Speed Prediction with Spatio–Temporal Correlation: A Deep Learning Approach
inferredcites →https://doi.org/10.48550/arxiv.1707.08110openalex-snapshot
Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4656006openalex-extracted
Unraveling the Winds of Change: Machine Learning Based Analysis and Forecasting of Wind Power Generation at Senegal's Taiba N'Diaye Wind Farm
inferred← citeshttps://doi.org/10.2139/ssrn.4691469openalex-extracted
Multi-Step Ahead Forecasting of Wind Vector for Multiple Wind Turbines Based on Novel Deep Learning Model
inferred← citeshttps://doi.org/10.2139/ssrn.4816325openalex-extracted
Short-Term Wind Speed Prediction Based on Singular Spectrum Analysis and Sample Convolution and Interaction Combined with Framework for Modal Migration
inferred← citeshttps://doi.org/10.1002/er.6679openalex-snapshot
A holistic review on energy forecasting using big data and deep learning models
inferred← citeshttps://doi.org/10.1002/ese3.1380openalex-snapshot
A novel interpretable model ensemble multivariate fast iterative filtering and temporal fusion transform for carbon price forecasting
inferred← citeshttps://doi.org/10.1002/ldr.70000openalex-snapshot
Attention Convolutional Neural Networks and Long Short‐Term Memory Model: Unveiling Spatiotemporal Dynamics of Ecological Indicators in Yili Mining Area
inferred← citeshttps://doi.org/10.1007/978-3-031-36999-5_27openalex-snapshot
Toward Active Control of Limit Cycle Oscillations in an Aeroelastic Wing Using a Variable Frequency Flow Disturbance Generator
inferred← citeshttps://doi.org/10.1007/s00477-022-02265-4openalex-snapshot
One-hour ahead wind speed forecasting using deep learning approach
inferred← citeshttps://doi.org/10.1007/s00477-022-02358-0openalex-snapshot
Short-term spatio-temporal forecasting of air temperatures using deep graph convolutional neural networks
inferred← citeshttps://doi.org/10.1007/s00500-020-05007-2openalex-snapshot
Stochastic recurrent wavelet neural network with EEMD method on energy price prediction
inferred← citeshttps://doi.org/10.1007/s10462-019-09768-7openalex-snapshot
A review of applications of artificial intelligent algorithms in wind farms
inferred← citeshttps://doi.org/10.1007/s10462-020-09838-1openalex-snapshot
A review on the long short-term memory model
inferred← citeshttps://doi.org/10.1007/s11356-021-17442-1openalex-snapshot
A systematic literature review of deep learning neural network for time series air quality forecasting
inferred← citeshttps://doi.org/10.1007/s11831-024-10182-8openalex-snapshot
A Survey of Artificial Intelligence Applications in Wind Energy Forecasting
inferred← citeshttps://doi.org/10.1007/s11831-025-10442-1openalex-snapshot
Optimizing Wind Energy Integration: A Review of Forecasting Techniques and Emerging Trends
inferred← citeshttps://doi.org/10.1007/s12145-023-01044-1openalex-snapshot
A hybrid forecasting model for very short-term wind speed prediction based on secondary decomposition and deep learning algorithms
inferred← citeshttps://doi.org/10.1007/s12517-021-06982-yopenalex-snapshot
Prediction of 10-min, hourly, and daily atmospheric air temperature: comparison of LSTM, ANFIS-FCM, and ARMA
inferred← citeshttps://doi.org/10.1007/s13131-021-1763-9openalex-snapshot
Multi-step ahead short-term predictions of storm surge level using CNN and LSTM network
inferred← citeshttps://doi.org/10.1007/s40515-022-00239-1openalex-snapshot
Ground Surface Displacements and Failure Mechanisms induced by EPB Shield Tunneling Method and Groundwater Levels Changes
inferred← citeshttps://doi.org/10.1007/s40747-024-01609-7openalex-snapshot
Integrating fast iterative filtering and ensemble neural network structure with attention mechanism for carbon price forecasting
inferred← citeshttps://doi.org/10.1016/b978-0-443-29104-3.00018-5openalex-snapshot
Machine learning techniques for the estimation of groundwater artificial recharge by conventional water
inferred← citeshttps://doi.org/10.1016/j.aej.2023.12.012openalex-snapshot
Machine learning-aided modeling for predicting freshwater production of a membrane desalination system: A long-short-term memory coupled with election-based optimizer
inferred← citeshttps://doi.org/10.1016/j.apenergy.2020.116405openalex-snapshot
Assessing the performance of deep learning models for multivariate probabilistic energy forecasting
inferred← citeshttps://doi.org/10.1016/j.apenergy.2021.116908openalex-snapshot
Super multi-step wind speed forecasting system with training set extension and horizontal–vertical integration neural network
inferred← citeshttps://doi.org/10.1016/j.apenergy.2021.117766openalex-snapshot
A review of wind speed and wind power forecasting with deep neural networks
inferred← citeshttps://doi.org/10.1016/j.apenergy.2022.118674openalex-snapshot
Deep learning combined wind speed forecasting with hybrid time series decomposition and multi-objective parameter optimization
inferred← citeshttps://doi.org/10.1016/j.apenergy.2022.119608openalex-snapshot
A hybrid attention-based deep learning approach for wind power prediction
inferred← citeshttps://doi.org/10.1016/j.apenergy.2024.123589openalex-snapshot
A new decomposition-ensemble strategy fusion with correntropy optimization learning algorithms for short-term wind speed prediction
inferred← citeshttps://doi.org/10.1016/j.apenergy.2024.123685openalex-snapshot
Sparse dynamic graph learning for district heat load forecasting
inferred← citeshttps://doi.org/10.1016/j.apenergy.2024.124492openalex-snapshot
Non-stationary GNNCrossformer: Transformer with graph information for non-stationary multivariate Spatio-Temporal wind power data forecasting
inferred← citeshttps://doi.org/10.1016/j.apenergy.2025.126016openalex-snapshot
A review of solar and wind energy forecasting: From single-site to multi-site paradigm
inferred← citeshttps://doi.org/10.1016/j.apenergy.2025.126419openalex-snapshot
Multi-dimensional data processing and intelligent forecasting technologies for renewable energy generation
inferred← citeshttps://doi.org/10.1016/j.atmosenv.2025.121491openalex-snapshot
Time series analysis and prediction of PM2.5 pollution concentration in Igdir province with deep learning models
inferred← citeshttps://doi.org/10.1016/j.compag.2022.107416openalex-snapshot
Gated recurrent unit models outperform other Machine learning models in prediction of minimum temperature in greenhouse Based on local weather data
inferred← citeshttps://doi.org/10.1016/j.egyai.2021.100060openalex-snapshot
A review and taxonomy of wind and solar energy forecasting methods based on deep learning
inferred← citeshttps://doi.org/10.1016/j.egyai.2024.100438openalex-snapshot
Federated learning and non-federated learning based power forecasting of photovoltaic/wind power energy systems: A systematic review
inferred← citeshttps://doi.org/10.1016/j.enbuild.2021.110998openalex-snapshot
Predicting hourly heating load in a district heating system based on a hybrid CNN-LSTM model
inferred← citeshttps://doi.org/10.1016/j.enconman.2019.06.083openalex-snapshot
Gaussian mixture model coupled recurrent neural networks for wind speed interval forecast
inferred← citeshttps://doi.org/10.1016/j.enconman.2019.111799openalex-snapshot
A review of deep learning for renewable energy forecasting
inferred← citeshttps://doi.org/10.1016/j.enconman.2019.112345openalex-snapshot
Application of hybrid model based on double decomposition, error correction and deep learning in short-term wind speed prediction
inferred← citeshttps://doi.org/10.1016/j.enconman.2020.112909openalex-snapshot
Taxonomy research of artificial intelligence for deterministic solar power forecasting
inferred← citeshttps://doi.org/10.1016/j.enconman.2020.112995openalex-snapshot
Wind speed forecasting using a new multi-factor fusion and multi-resolution ensemble model with real-time decomposition and adaptive error correction
inferred← citeshttps://doi.org/10.1016/j.enconman.2020.113085openalex-snapshot
Improved quantile convolutional neural network with two-stage training for daily-ahead probabilistic forecasting of photovoltaic power
inferred← citeshttps://doi.org/10.1016/j.enconman.2021.115036openalex-snapshot
Ultra-short term wind power prediction applying a novel model named SATCN-LSTM
inferred← citeshttps://doi.org/10.1016/j.enconman.2022.115433openalex-snapshot
Deep non-crossing probabilistic wind speed forecasting with multi-scale features
inferred← citeshttps://doi.org/10.1016/j.enconman.2022.115590openalex-snapshot
Quaternion convolutional long short-term memory neural model with an adaptive decomposition method for wind speed forecasting: North aegean islands case studies
inferred← citeshttps://doi.org/10.1016/j.energy.2019.116316openalex-snapshot
A cascaded deep learning wind power prediction approach based on a two-layer of mode decomposition
inferred← citeshttps://doi.org/10.1016/j.energy.2019.116498openalex-snapshot
Day ahead powerful probabilistic wind power forecast using combined intelligent structure and fuzzy clustering algorithm
inferred← citeshttps://doi.org/10.1016/j.energy.2020.118403openalex-snapshot
Thermal power forecasting of solar power tower system by combining mechanism modeling and deep learning method
inferred← citeshttps://doi.org/10.1016/j.energy.2020.118441openalex-snapshot
Day-ahead spatiotemporal wind speed forecasting using robust design-based deep learning neural network
inferred← citeshttps://doi.org/10.1016/j.energy.2020.119180openalex-snapshot
Short-term wind speed time series forecasting based on a hybrid method with multiple objective optimization for non-convex target
inferred← citeshttps://doi.org/10.1016/j.energy.2020.119361openalex-snapshot
A combined forecasting system based on statistical method, artificial neural networks, and deep learning methods for short-term wind speed forecasting
inferred← citeshttps://doi.org/10.1016/j.energy.2021.120842openalex-snapshot
An investigation on deep learning and wavelet transform to nowcast wind power and wind power ramp: A case study in Brazil and Uruguay
inferred← citeshttps://doi.org/10.1016/j.energy.2021.121306openalex-snapshot
Short-term probabilistic predictions of wind multi-parameter based on one-dimensional convolutional neural network with attention mechanism and multivariate copula distribution estimation
inferred← citeshttps://doi.org/10.1016/j.energy.2021.121492openalex-snapshot
A novel asynchronous deep reinforcement learning model with adaptive early forecasting method and reward incentive mechanism for short-term load forecasting
inferred← citeshttps://doi.org/10.1016/j.energy.2021.121795openalex-snapshot
A hybrid deep learning architecture for wind power prediction based on bi-attention mechanism and crisscross optimization
inferred← citeshttps://doi.org/10.1016/j.energy.2021.122116openalex-snapshot
Using deep learning and meteorological parameters to forecast the photovoltaic generators intra-hour output power interval for smart grid control
inferred← citeshttps://doi.org/10.1016/j.energy.2022.123761openalex-snapshot
Wind speed prediction based on multi-variable Capsnet-BILSTM-MOHHO for WPCCC
inferred← citeshttps://doi.org/10.1016/j.energy.2022.123785openalex-snapshot
Wind speed estimation using novelty hybrid adaptive estimation model based on decomposition and deep learning methods (ICEEMDAN-CNN)
inferred← citeshttps://doi.org/10.1016/j.energy.2022.123990openalex-snapshot
Interpretable wind speed prediction with multivariate time series and temporal fusion transformers
inferred← citeshttps://doi.org/10.1016/j.energy.2022.124095openalex-snapshot
Short-term wind speed forecasting based on spatial-temporal graph transformer networks
inferred← citeshttps://doi.org/10.1016/j.energy.2022.124889openalex-snapshot
Forecasting monthly gas field production based on the CNN-LSTM model
inferred← citeshttps://doi.org/10.1016/j.energy.2022.126100openalex-snapshot
Multivariate wind speed forecasting based on multi-objective feature selection approach and hybrid deep learning model
inferred← citeshttps://doi.org/10.1016/j.energy.2022.126190openalex-snapshot
Outlet water temperature prediction of energy pile based on spatial-temporal feature extraction through CNN–LSTM hybrid model
inferred← citeshttps://doi.org/10.1016/j.energy.2023.127678openalex-snapshot
A transformer-based deep neural network with wavelet transform for forecasting wind speed and wind energy
inferred← citeshttps://doi.org/10.1016/j.energy.2023.128945openalex-snapshot
An adaptive variational mode decomposition for wind power prediction using convolutional block attention deep learning network
inferred← citeshttps://doi.org/10.1016/j.energy.2023.129728openalex-snapshot
Two-stage decomposition and temporal fusion transformers for interpretable wind speed forecasting
inferred← citeshttps://doi.org/10.1016/j.energy.2023.129823openalex-snapshot
A novel spatio-temporal wind speed forecasting method based on the microscale meteorological model and a hybrid deep learning model
inferred← citeshttps://doi.org/10.1016/j.energy.2024.130751openalex-snapshot
An ultra-short-term wind power prediction method based on spatial-temporal attention graph convolutional model
inferred← citeshttps://doi.org/10.1016/j.energy.2024.130854openalex-snapshot
A novel model for ultra-short term wind power prediction based on Vision Transformer
inferred← citeshttps://doi.org/10.1016/j.energy.2024.131964openalex-snapshot
Multi-step ahead forecasting of wind vector for multiple wind turbines based on new deep learning model
inferred← citeshttps://doi.org/10.1016/j.energy.2024.132122openalex-snapshot
Meta W ave L earner: Predicting wave farms power output using effective meta-learner deep gradient boosting model: A case study from Australian coasts
inferred← citeshttps://doi.org/10.1016/j.energy.2024.133072openalex-snapshot
FedWindT: Federated learning assisted transformer architecture for collaborative and secure wind power forecasting in diverse conditions
inferred← citeshttps://doi.org/10.1016/j.energy.2024.133208openalex-snapshot
Enhanced offshore wind resource assessment using hybrid data fusion and numerical models
inferred← citeshttps://doi.org/10.1016/j.energy.2025.138275openalex-snapshot
Wind power forecasting for newly built wind farms based on deep learning with dual-stage attention mechanism and adaptive transfer learning
inferred← citeshttps://doi.org/10.1016/j.engappai.2020.104133openalex-snapshot
Current status of hybrid structures in wind forecasting
inferred← citeshttps://doi.org/10.1016/j.engappai.2023.105987openalex-snapshot
Wind speed interval prediction based on multidimensional time series of Convolutional Neural Networks
inferred← citeshttps://doi.org/10.1016/j.eprime.2026.201235openalex-snapshot
Robust resilient scheduling of interconnected smart energy hubs considering LSTM-based disaster probability prediction
inferred← citeshttps://doi.org/10.1016/j.epsr.2020.106922openalex-snapshot
Componentnet: Processing U- and V-components for spatio-Temporal wind speed forecasting
inferred← citeshttps://doi.org/10.1016/j.epsr.2022.108765openalex-snapshot
A Wind Speed Combination Forecasting Method Based on Multifaceted Feature Fusion and Transfer Learning for Centralized Control Center
inferred← citeshttps://doi.org/10.1016/j.epsr.2025.112196openalex-snapshot
Adaptive multi-scale short term wind power forecasting framework based on TimeMixer and Mix-of-Experts
inferred← citeshttps://doi.org/10.1016/j.esd.2022.02.002openalex-snapshot
An analysis of different deep learning neural networks for intra-hour solar irradiation forecasting to compute solar photovoltaic generators' energy production
inferred← citeshttps://doi.org/10.1016/j.eswa.2021.115272openalex-snapshot
A novel trilinear deep residual network with self-adaptive Dropout method for short-term load forecasting
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.119878openalex-snapshot
Decomposition-based wind speed forecasting model using causal convolutional network and attention mechanism
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.127436openalex-snapshot
Prompting large language model for multi-location multi-step zero-shot wind power forecasting
inferred← citeshttps://doi.org/10.1016/j.gsf.2021.101177openalex-snapshot
Modelling the performance of EPB shield tunnelling using machine and deep learning algorithms
inferred← citeshttps://doi.org/10.1016/j.ijepes.2021.107777openalex-snapshot
Forecasting intra-hour solar photovoltaic energy by assembling wavelet based time-frequency analysis with deep learning neural networks
inferred← citeshttps://doi.org/10.1016/j.ijepes.2025.110513openalex-snapshot
Graph attention convolution network for power flow calculation considering grid uncertainty
inferred← citeshttps://doi.org/10.1016/j.ijforecast.2020.10.007openalex-snapshot
U-Convolutional model for spatio-temporal wind speed forecasting
inferred← citeshttps://doi.org/10.1016/j.inffus.2025.103504openalex-snapshot
DUSTFN: A dual-path U spatiotemporal fusion network for wind speed prediction
inferred← citeshttps://doi.org/10.1016/j.ins.2020.08.053openalex-snapshot
A novel ensemble deep learning model with dynamic error correction and multi-objective ensemble pruning for time series forecasting
inferred← citeshttps://doi.org/10.1016/j.istruc.2026.112118openalex-snapshot
A combined vibration-machine learning method for structural performance assessment of modular supporting structure
inferred← citeshttps://doi.org/10.1016/j.jclepro.2021.128566openalex-snapshot
Deep learning models for solar irradiance forecasting: A comprehensive review
inferred← citeshttps://doi.org/10.1016/j.jweia.2024.105898openalex-snapshot
Short-term wind speed forecasting using multivariate pretreatment technique and correntropy loss-enhanced selective combination
inferred← citeshttps://doi.org/10.1016/j.jweia.2025.106035openalex-snapshot
Short-term extreme wind speed forecasting using dual-output LSTM-based regression and classification model
inferred← citeshttps://doi.org/10.1016/j.knosys.2021.107403openalex-snapshot
Spatiotemporal fuzzy-graph convolutional network model with dynamic feature encoding for traffic forecasting
inferred← citeshttps://doi.org/10.1016/j.knosys.2022.109028openalex-snapshot
Dynamic graph convolutional networks based on spatiotemporal data embedding for traffic flow forecasting
inferred← citeshttps://doi.org/10.1016/j.ref.2025.100739openalex-snapshot
A review of data-driven deep learning models for solar and wind energy forecasting
inferred← citeshttps://doi.org/10.1016/j.renene.2020.05.150openalex-snapshot
Short-term global horizontal irradiance forecasting based on a hybrid CNN-LSTM model with spatiotemporal correlations
inferred← citeshttps://doi.org/10.1016/j.renene.2021.04.091openalex-snapshot
Hybrid wind speed forecasting model based on multivariate data secondary decomposition approach and deep learning algorithm with attention mechanism
inferred← citeshttps://doi.org/10.1016/j.renene.2021.05.023openalex-snapshot
Spatio-temporal wind speed prediction of multiple wind farms using capsule network
inferred← citeshttps://doi.org/10.1016/j.renene.2022.02.095openalex-snapshot
Wind speed forecasting using multi-site collaborative deep learning for complex terrain application in valleys
inferred← citeshttps://doi.org/10.1016/j.renene.2022.04.055openalex-snapshot
Spatio-temporal wind speed prediction based on Clayton Copula function with deep learning fusion
inferred← citeshttps://doi.org/10.1016/j.renene.2022.07.125openalex-snapshot
Wind speed forecasting with correlation network pruning and augmentation: A two-phase deep learning method
inferred← citeshttps://doi.org/10.1016/j.renene.2022.09.036openalex-snapshot
Promoting wind energy for sustainable development by precise wind speed prediction based on graph neural networks
inferred← citeshttps://doi.org/10.1016/j.renene.2022.09.114openalex-snapshot
A combined short-term wind speed forecasting model based on CNN–RNN and linear regression optimization considering error
inferred← citeshttps://doi.org/10.1016/j.renene.2022.12.121openalex-snapshot
Dynamic multi-turbines spatiotemporal correlation model enabled digital twin technology for real-time wind speed prediction
inferred← citeshttps://doi.org/10.1016/j.renene.2023.03.094openalex-snapshot
Probabilistic spatiotemporal forecasting of wind speed based on multi-network deep ensembles method
inferred← citeshttps://doi.org/10.1016/j.renene.2023.119101openalex-snapshot
Rolling decomposition method in fusion with echo state network for wind speed forecasting
inferred← citeshttps://doi.org/10.1016/j.renene.2024.120367openalex-snapshot
A novel solar irradiance forecasting method based on multi-physical process of atmosphere optics and LSTM-BP model
inferred← citeshttps://doi.org/10.1016/j.renene.2026.126249openalex-snapshot
Data-driven artificial intelligence for wind speed forecasting: A decade review and multi-site benchmark for operational wind energy applications
inferred← citeshttps://doi.org/10.1016/j.resconrec.2026.108777openalex-snapshot
Global meta-analysis of bioenergy crops reveals substantial greenhouse gas mitigation potential
inferred← citeshttps://doi.org/10.1016/j.ress.2026.112777openalex-snapshot
Deep learning-based failure rate prediction of sewer networks with uncertainty quantification under climatic variations: A Hong Kong case study
inferred← citeshttps://doi.org/10.1016/j.rser.2020.110591openalex-snapshot
A deep learning framework for building energy consumption forecast
inferred← citeshttps://doi.org/10.1016/j.segan.2023.101019openalex-snapshot
Short-term Forecasting Approach Based on bidirectional long short-term memory and convolutional neural network for Regional Photovoltaic Power Plants
inferred← citeshttps://doi.org/10.1016/j.tust.2022.104405openalex-snapshot
Deep learning analysis for energy consumption of shield tunneling machine drive system
inferred← citeshttps://doi.org/10.1016/j.undsp.2024.09.004openalex-snapshot
Reliable prediction for TBM energy consumption during tunnel excavation: A novel technique balancing explainability and performance
inferred← citeshttps://doi.org/10.1016/j.ymssp.2023.110715openalex-snapshot
A vibration-based 1DCNN-BiLSTM model for structural state recognition of RC beams
inferred← citeshttps://doi.org/10.1038/s41467-025-58456-4openalex-snapshot
A machine learning model for hub-height short-term wind speed prediction
inferred← citeshttps://doi.org/10.1038/s41598-025-10641-7openalex-snapshot
Chaotic billiards optimized hybrid transformer and XGBoost model for robust and sustainable time series forecasting
inferred← citeshttps://doi.org/10.1049/cit2.12076openalex-snapshot
A comprehensive review on deep learning approaches in wind forecasting applications
inferred← citeshttps://doi.org/10.1049/rpg2.12085openalex-snapshot
Ultra‐short‐term multi‐step wind power forecasting based on CNN‐LSTM
inferred← citeshttps://doi.org/10.1061/(asce)ey.1943-7897.0000823openalex-snapshot
Enhanced Probabilistic Spatiotemporal Wind Speed Forecasting Based on Deep Learning, Quantile Regression, and Error Correction
inferred← citeshttps://doi.org/10.1063/5.0062790openalex-snapshot
A novel hybrid forecasting system based on data augmentation and deep learning neural network for short-term wind speed forecasting
inferred← citeshttps://doi.org/10.1063/5.0153298openalex-snapshot
Ultra-short-term wind speed prediction based on deep spatial-temporal residual network
inferred← citeshttps://doi.org/10.1063/5.0165151openalex-snapshot
An attention mechanism based deep nonlinear ensemble paradigm of strengthened feature extraction method for wind power prediction
inferred← citeshttps://doi.org/10.1063/5.0212699openalex-snapshot
Ultra-short-term wind power forecasting method based on multi-variable joint extraction of spatial-temporal features
inferred← citeshttps://doi.org/10.1080/0951192x.2025.2478011openalex-snapshot
A multi-dimensional data integration approach for machining system multi-level energy consumption modeling and prediction
inferred← citeshttps://doi.org/10.1080/15435075.2025.2509118openalex-snapshot
On the accuracy of Long Short Term Memory (LSTM) in solar irradiance forecasting: A meta-analysis and meta-regression
inferred← citeshttps://doi.org/10.1080/15567036.2021.1925379openalex-snapshot
Application of stacked and bidirectional long short-term memory deep learning models for wind speed forecasting at an offshore site
inferred← citeshttps://doi.org/10.1080/15567036.2024.2392890openalex-snapshot
Machine learning approaches in predicting the wind power output and turbine rotational speed in a wind farm
inferred← citeshttps://doi.org/10.1088/1742-6596/1659/1/012039openalex-snapshot
Probabilistic Wind Speed Forecasting based on Minimal Gated Unit and Quantile Regression
inferred← citeshttps://doi.org/10.1109/access.2020.3004284openalex-snapshot
Forecasting Stock Prices Using a Hybrid Deep Learning Model Integrating Attention Mechanism, Multi-Layer Perceptron, and Bidirectional Long-Short Term Memory Neural Network
inferred← citeshttps://doi.org/10.1109/access.2023.3323694openalex-snapshot
Automatic Recognition of Illegal Substations by Employing Logit-Boost Algorithm and LSTM With the Help of Different Landsat-8 OLI Image Spectral Band Parameters: A Case Study in Sason, Turkey
inferred← citeshttps://doi.org/10.1109/access.2023.3333895openalex-snapshot
A Multistage Hybrid Deep Learning Model for Enhanced Solar Tracking
inferred← citeshttps://doi.org/10.1109/access.2024.3457380openalex-snapshot
The IVMD-CNN-GRU-Attention Model for Wind Power Prediction With Sample Entropy Fusion
inferred← citeshttps://doi.org/10.1109/access.2025.3586997openalex-snapshot
Spatiotemporal Wind Energy Forecasting: A Comprehensive Survey and a Deep Equilibrium-Based Case Study With StemGNN
inferred← citeshttps://doi.org/10.1109/access.2025.3603920openalex-snapshot
Air Quality Prediction via Embedded ML/DL and Quantized Models
inferred← citeshttps://doi.org/10.1109/bigdia56350.2022.9874126openalex-snapshot
Short-term Forecast of Wind Speed Based on Hybrid Multi-Stage Decomposition and LSTM Optimized by an Improved WOA
inferred← citeshttps://doi.org/10.1109/cieec50170.2021.9510691openalex-snapshot
Wind Speed Prediction for Wind Farm Based on Clayton Copula Function and Deep Learning Fusion
inferred← citeshttps://doi.org/10.1109/ias54023.2022.9939731openalex-snapshot
Ultra-short-term Power Forecasting of Wind Farm Cluster Based on Spatio-temporal Graph Neural Network Pattern Prediction
inferred← citeshttps://doi.org/10.1109/iccams60113.2023.10526008openalex-snapshot
Evaluation Of Renewable Energy Forecasting (REF) Technique Using by Machine Learning
inferred← citeshttps://doi.org/10.1109/icecet55527.2022.9872844openalex-snapshot
Self-supervised spatial-temporal prediction of multi-source sensor data for power systems
inferred← citeshttps://doi.org/10.1109/icei63732.2024.10917265openalex-snapshot
Weather Embedding Cluster Transformer for Solar Irradiance Prediction
inferred← citeshttps://doi.org/10.1109/icitri59340.2023.10249864openalex-snapshot
Air Quality Estimation with Embedded AI-Based Prediction Algorithms
inferred← citeshttps://doi.org/10.1109/icpds54746.2021.9689926openalex-snapshot
Research on Wind Speed Forecasting Method of Wind Farm Based on Whale Optimization Algorithm-Hybrid Copula Function Correlation Analysis
inferred← citeshttps://doi.org/10.1109/icpre55555.2022.9960327openalex-snapshot
Short-term Interval Prediction of Wind Speed Using LSTM with Improved Grid Search
inferred← citeshttps://doi.org/10.1109/jiot.2022.3150048openalex-snapshot
Data-Correlation-Aware Unsupervised Deep-Learning Model for Anomaly Detection in Cyber–Physical Systems
inferred← citeshttps://doi.org/10.1109/jsyst.2019.2961172openalex-snapshot
A New Combinatory Approach for Wind Power Forecasting
inferred← citeshttps://doi.org/10.1109/naps56150.2022.10012249openalex-snapshot
Deep Learning Model with Probability Density Function and Feature Engineering for Short Term Wind Speed Prediction
inferred← citeshttps://doi.org/10.1109/tia.2023.3321267openalex-snapshot
Spatio-Temporal Graph Neural Network and Pattern Prediction Based Ultra-Short-Term Power Forecasting of Wind Farm Cluster
inferred← citeshttps://doi.org/10.1109/tii.2021.3063530openalex-snapshot
Augmented Convolutional Network for Wind Power Prediction: A New Recurrent Architecture Design With Spatial-Temporal Image Inputs
inferred← citeshttps://doi.org/10.1109/tim.2023.3267343openalex-snapshot
Multistate Prediction for In-Service Gas Turbine via Adaptive Diffusion Graph Network
inferred← citeshttps://doi.org/10.1109/tim.2023.3324005openalex-snapshot
Layered-Vine Copula-Based Wind Speed Prediction Using Spatial Correlation and Meteorological Influence
inferred← citeshttps://doi.org/10.1109/tkde.2021.3118389openalex-snapshot
Multivariate Correlation Matrix-Based Deep Learning Model With Enhanced Heuristic Optimization for Short-Term Traffic Forecasting
inferred← citeshttps://doi.org/10.1109/tpwrs.2021.3105101openalex-snapshot
Generative Probabilistic Wind Speed Forecasting: A Variational Recurrent Autoencoder Based Method
inferred← citeshttps://doi.org/10.1109/tste.2021.3135278openalex-snapshot
A Deep Attention Convolutional Recurrent Network Assisted by K-Shape Clustering and Enhanced Memory for Short Term Wind Speed Predictions
inferred← citeshttps://doi.org/10.1111/joes.70005openalex-snapshot
Recent Hybrid Machine Learning Approaches in Wind Speed Forecasting—A Review
inferred← citeshttps://doi.org/10.1115/1.4048001openalex-snapshot
Online Chatter Detection for Milling Operations Using LSTM Neural Networks Assisted by Motor Current Signals of Ball Screw Drives
inferred← citeshttps://doi.org/10.1117/12.3059971openalex-snapshot
Short-term wind power prediction based on improved back propagation neural network
inferred← citeshttps://doi.org/10.1145/3586006openalex-snapshot
Deep Learning for Variable Renewable Energy: A Systematic Review
inferred← citeshttps://doi.org/10.1145/3605801.3605841openalex-snapshot
LSTM-GATs: Wind field prediction based on graph attention deep neural network
inferred← citeshttps://doi.org/10.1145/3766546openalex-snapshot
A Survey on Spatio-Temporal Prediction: From Transformers to Foundation Models
inferred← citeshttps://doi.org/10.1155/2020/4057630openalex-snapshot
Evaluation Method of Wind Speed Time-Shifting Characteristics at Multiple Scales and Its Application in Wind Power System
inferred← citeshttps://doi.org/10.1155/2020/7854286openalex-snapshot
An Advanced Hybrid Forecasting System for Wind Speed Point Forecasting and Interval Forecasting
inferred← citeshttps://doi.org/10.1177/0309524x221106184openalex-snapshot
A STL decomposition-based deep neural networks for offshore wind speed forecasting
inferred← citeshttps://doi.org/10.1177/0309524x261486994openalex-snapshot
Operational assessment of deep learning-based multi-horizon wind speed forecasting for wind energy applications
inferred← citeshttps://doi.org/10.1177/0958305x241228515openalex-snapshot
Wind speed and wind power forecasting models
inferred← citeshttps://doi.org/10.1177/13872877261446573openalex-snapshot
Early diagnosis of Alzheimer's disease through handwriting analysis and deep learning: A review
inferred← citeshttps://doi.org/10.12677/aep.2025.159135openalex-snapshot
Regional-Scale Dispersion and Concentration Prediction of Emerging Pollutants: From Mechanistic Models to Intelligent Algorithms
inferred← citeshttps://doi.org/10.1515/ijeeps-2025-0005openalex-snapshot
Data-driven wind power prediction model based on improved generative adversarial network
inferred← citeshttps://doi.org/10.21203/rs.3.rs-871753/v1openalex-snapshot
A Combined Model Based on Society Cognitive Optimization Algorithm for Wind Speed Forecasting
inferred← citeshttps://doi.org/10.2514/6.2024-2528openalex-snapshot
Utilizing Machine Learning to Predict Limit Cycle Oscillation Characteristics in Aeroelastic Wing
inferred← citeshttps://doi.org/10.3233/jifs-210657openalex-snapshot
A novel hybrid deep learning model for taxi demand forecasting based on decomposition of time series and fusion of text data
inferred← citeshttps://doi.org/10.32604/ee.2023.040887openalex-snapshot
The Short-Term Prediction of Wind Power Based on the Convolutional Graph Attention Deep Neural Network
inferred← citeshttps://doi.org/10.3389/feart.2025.1580945openalex-snapshot
Ultra-short-term prediction of spatio-temporal wind speed based on a hybrid deep learning model
inferred← citeshttps://doi.org/10.3390/app11094129openalex-snapshot
A Novel Deep Learning Based Model for Tropical Intensity Estimation and Post-Disaster Management of Hurricanes
inferred← citeshttps://doi.org/10.3390/app13179888openalex-snapshot
Short-Term Wind Power Forecasting Based on VMD and a Hybrid SSA-TCN-BiGRU Network
inferred← citeshttps://doi.org/10.3390/app15073507openalex-snapshot
Anomaly Detection Method Considering PLC Control Logic Structure for ICS Cyber Threat Detection
inferred← citeshttps://doi.org/10.3390/electronics14132566openalex-snapshot
A Dual-Branch Transformer Network with Multi-Scale Attention Mechanism for Microgrid Wind Turbine Power Forecasting
inferred← citeshttps://doi.org/10.3390/en13133440openalex-snapshot
Localized Convolutional Neural Networks for Geospatial Wind Forecasting
inferred← citeshttps://doi.org/10.3390/en15155472openalex-snapshot
A Multi-Hour Ahead Wind Power Forecasting System Based on a WRF-TOPSIS-ANFIS Model
inferred← citeshttps://doi.org/10.3390/en16031530openalex-snapshot
Artificial Intelligence and Machine Learning in Grid Connected Wind Turbine Control Systems: A Comprehensive Review
inferred← citeshttps://doi.org/10.3390/en16041841openalex-snapshot
A Hybrid Neural Network Model for Short-Term Wind Speed Forecasting
inferred← citeshttps://doi.org/10.3390/en16052307openalex-snapshot
A Comprehensive Review of Shipboard Power Systems with New Energy Sources
inferred← citeshttps://doi.org/10.3390/en17020384openalex-snapshot
Interpretable Wind Power Short-Term Power Prediction Model Using Deep Graph Attention Network
inferred← citeshttps://doi.org/10.3390/en18051158openalex-snapshot
Wind Turbine Fault Diagnosis with Imbalanced SCADA Data Using Generative Adversarial Networks
inferred← citeshttps://doi.org/10.3390/en18112675openalex-snapshot
Quarter-Hourly Power Load Forecasting Based on a Hybrid CNN-BiLSTM-Attention Model with CEEMDAN, K-Means, and VMD
inferred← citeshttps://doi.org/10.3390/en19143406openalex-snapshot
Adaptive Multi-Branch Heterogeneous Fusion Network for Wind Vector Prediction
inferred← citeshttps://doi.org/10.3390/engproc2021005039openalex-snapshot
Decomposition-Based Hybrid Models for Very Short-Term Wind Power Forecasting
inferred← citeshttps://doi.org/10.3390/jmse14141290openalex-snapshot
Physics-Guided Deep Learning for Short-Term Offshore Wind Power Forecasting
inferred← citeshttps://doi.org/10.3390/math12132105openalex-snapshot
Wind Energy Production in Italy: A Forecasting Approach Based on Fractional Brownian Motion and Generative Adversarial Networks
inferred← citeshttps://doi.org/10.3390/pr10040689openalex-snapshot
A Combined Model Based on the Social Cognitive Optimization Algorithm for Wind Speed Forecasting
inferred← citeshttps://doi.org/10.3390/pr12102185openalex-snapshot
A Predictive Model for Sintering Ignition Temperature Based on a CNN-LSTM Neural Network with an Attention Mechanism
inferred← citeshttps://doi.org/10.3390/rs12213671openalex-snapshot
The Ultra-Short-Term Forecasting of Global Horizonal Irradiance Based on Total Sky Images
inferred← citeshttps://doi.org/10.3390/su132212493openalex-snapshot
Comparison of the Deep Learning Performance for Short-Term Power Load Forecasting
inferred← citeshttps://doi.org/10.3390/su142013339openalex-snapshot
Automatic Selection of Temperature Variables for Short-Term Load Forecasting
inferred← citeshttps://doi.org/10.3390/su15075871openalex-snapshot
Spatio-Temporal Wind Speed Prediction Based on Improved Residual Shrinkage Network
inferred← citeshttps://doi.org/10.3390/w15061128openalex-snapshot
Data-Driven Parameter Prediction of Water Pumping Station
showing the first 200 of 210 · page through all 210
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.