Research graph
References from M-DCATDGN: Enhancing load demand forecasting with an adaptive dynamic graph neural network. Local targets link to admitted publications; unresolved targets remain external evidence.
Optimization of multi-reservoir operation with a new hedging rule: application of fuzzy set theory and NSGA-II
10.1007/s13201-016-0434-z · 2017 · External reference
Surface water sodium (Na+) concentration prediction using hybrid weighted exponential regression model with gradient-based optimization
10.1007/s11356-022-19300-0 · 2022 · External reference
Assessment of the hedging policy on reservoir operation for future drought conditions under climate change
10.1007/s10584-020-02672-y · 2020 · External reference
A review of short term load forecasting using artificial neural network models
10.1016/j.procs.2015.04.160 · 2015 · External reference
Artificial neural network and SARIMA based models for power load forecasting in Turkish electricity market
10.1371/journal.pone.0175915 · 2017 · External reference
Day-ahead building-level load forecasts using deep learning vs. traditional time-series techniques
10.1016/j.apenergy.2018.12.042 · 2019 · External reference
An adaptive ensemble framework with representative subset based weight correction for short-term forecast of peak power load
10.1016/j.apenergy.2022.120156 · 2022 · External reference
New approaches for calculating Moran’s index of spatial autocorrelation
2013 · External reference
Regression-SARIMA modelling of daily peak electricity demand in South Africa
10.17159/2413-3051/2012/v23i3a3169 · 2012 · External reference
Short-term city electric load forecasting with considering temperature effects: An improved ARIMAX model
2015 · External reference
Modeling and forecasting hourly electricity demand by SARIMAX with interactions
10.1016/j.energy.2018.09.157 · 2018 · External reference
A hybrid model for deep learning short-term power load forecasting based on feature extraction statistics techniques
10.1016/j.eswa.2023.122012 · 2024 · External reference
10.1145/3447548.3467430
10.1145/3447548.3467430 · External reference
A hybrid method based on wavelet, ANN and ARIMA model for short-term load forecasting
10.1080/0952813x.2013.813976 · 2014 · External reference
A short-term integrated wind speed prediction system based on fuzzy set feature extraction and intelligent optimization
10.1016/j.compind.2025.104418 · 2026 · External reference
A global modeling framework for load forecasting in distribution networks
10.1109/tsg.2023.3264525 · 2023 · External reference
Attention based spatial-temporal graph convolutional networks for traffic flow forecasting
2019 · External reference
A short-term load forecasting model of multi-scale CNN-LSTM hybrid neural network considering the real-time electricity price
10.1016/j.egyr.2020.11.078 · 2020 · External reference
Electric load forecasting based on deep learning and optimized by heuristic algorithm in smart grid
10.1016/j.apenergy.2020.114915 · 2020 · External reference
Inductive representation learning on large graphs
2017 · External reference
Methods and models for electric load forecasting: a comprehensive review
10.2478/jlst-2020-0004 · 2020 · External reference
A novel interval-valued carbon price forecasting paradigm: multi-factor intelligent recognition-based ensemble learning
10.1016/j.compind.2025.104352 · 2025 · External reference
Spatial load forecasting of electric vehicle charging using GIS and diffusion theory
2017 · External reference
Review of load forecasting based on artificial intelligence methodologies, models, and challenges
10.1016/j.epsr.2022.108067 · 2022 · External reference
Power load forecasting based on spatial–temporal fusion graph convolution network
10.1016/j.techfore.2024.123435 · 2024 · External reference
Probabilistic electricity price forecasting based on penalized temporal fusion transformer
10.1002/for.3084 · 2024 · External reference
A new ARIMA model for hourly load forecasting
1999 · External reference
Unresolved reference
External reference
Unresolved reference
2016 · External reference
Short-term residential load forecasting based on LSTM recurrent neural network
10.1109/tsg.2017.2753802 · 2017 · External reference
Forecasting water quality indices using generalized ridge model, regularized weighted kernel ridge model, and optimized multivariate variational mode decomposition
10.1038/s41598-025-99341-w · 2025 · External reference
Load forecasting of andhra pradesh grid using PSO, DE algorithms
2012 · External reference
Electrical load forecasting models: A critical systematic review
10.1016/j.scs.2017.08.009 · 2017 · External reference
Reliability evaluation of wind power systems by integrating granularity-related latin hypercube sampling with LSTM-based prediction
10.1016/j.compind.2025.104365 · 2025 · External reference
Spatial-temporal residential short-term load forecasting via graph neural networks
10.1109/tsg.2021.3093515 · 2021 · External reference
A spatial multi-resolution multi-objective data-driven ensemble model for multi-step air quality index forecasting based on real-time decomposition
10.1016/j.compind.2020.103387 · 2021 · External reference
Graph Convolutional Networks based short-term load forecasting: Leveraging spatial information for improved accuracy
10.1016/j.epsr.2024.110263 · 2024 · External reference
Electricity demand forecasting at distribution and household levels using explainable causal graph neural network
10.1016/j.egyai.2024.100368 · 2024 · External reference
Electricity load forecasting: a systematic review
2020 · External reference
Unresolved reference
2019 · External reference
Short-term load forecasting based on CEEMDAN and Transformer
10.1016/j.epsr.2022.108885 · 2023 · External reference
Optimization algorithms surpassing metaphor
2022 · External reference
A hybrid machine learning model for forecasting a billing period’s peak electric load days
10.1016/j.ijforecast.2019.03.025 · 2019 · External reference
Intelligent crude oil price probability forecasting: Deep learning models and industry applications
10.1016/j.compind.2024.104150 · 2024 · External reference
Deep learning for household load forecasting—A novel pooling deep RNN
10.1109/tsg.2017.2686012 · 2017 · External reference
Data driven day-ahead electrical load forecasting through repeated wavelet transform assisted SVM model
2021 · External reference
An association rule-assisted multi-time-series forecasting method for non-production material consumption in the automotive sector
10.1016/j.compind.2025.104366 · 2025 · External reference
Graph convolutional network-based aggregated demand response baseline load estimation
10.1016/j.energy.2022.123847 · 2022 · External reference
Integrated approaches in resilient hierarchical load forecasting via TCN and optimal valley filling based demand response application
10.1016/j.apenergy.2024.122722 · 2024 · External reference
Unresolved reference
2018 · External reference
Attention is all you need
2017 · External reference
Short-term power load forecasting for combined heat and power using CNN-LSTM enhanced by attention mechanism
10.1016/j.energy.2023.128274 · 2023 · External reference
Electrical load forecasting based on variable T-distribution and dual attention mechanism
10.1016/j.energy.2023.128569 · 2023 · External reference
A transformer-based method of multienergy load forecasting in integrated energy system
10.1109/tsg.2022.3166600 · 2022 · External reference
Efficient residential electric load forecasting via transfer learning and graph neural networks
10.1109/tsg.2022.3208211 · 2022 · External reference
A comprehensive survey on graph neural networks
10.1109/tnnls.2020.2978386 · 2020 · External reference
Unresolved reference
2019 · External reference
Forecasting day-ahead electricity prices with spatial dependence
10.1016/j.ijforecast.2023.11.006 · 2024 · External reference
Global electricity demand forecasting for multi-consumer retailers using a decomposition-based multi-sight convolutional neural network
10.1016/j.compind.2025.104415 · 2026 · External reference
Multi-temporal-spatial-scale temporal convolution network for short-term load forecasting of power systems
10.1016/j.apenergy.2020.116328 · 2021 · External reference
Unresolved reference
2015 · External reference
Are transformers effective for time series forecasting?
2023 · External reference
Energy consumption forecasting in non-stationary machining processes based on a physics-guided transformer
10.1016/j.compind.2025.104321 · 2025 · External reference
Graph neural networks: A review of methods and applications
10.1016/j.aiopen.2021.01.001 · 2020 · External reference
Probabilistic electricity price forecasting based on penalized temporal fusion transformer
10.1002/for.3084 · ExternalCitation · doi-reference
Assessment of the hedging policy on reservoir operation for future drought conditions under climate change
10.1007/s10584-020-02672-y · ExternalCitation · doi-reference
Surface water sodium (Na+) concentration prediction using hybrid weighted exponential regression model with gradient-based optimization
10.1007/s11356-022-19300-0 · ExternalCitation · doi-reference
Optimization of multi-reservoir operation with a new hedging rule: application of fuzzy set theory and NSGA-II
10.1007/s13201-016-0434-z · ExternalCitation · doi-reference
Graph neural networks: A review of methods and applications
10.1016/j.aiopen.2021.01.001 · ExternalCitation · doi-reference
Day-ahead building-level load forecasts using deep learning vs. traditional time-series techniques
10.1016/j.apenergy.2018.12.042 · ExternalCitation · doi-reference
Electric load forecasting based on deep learning and optimized by heuristic algorithm in smart grid
10.1016/j.apenergy.2020.114915 · ExternalCitation · doi-reference
Multi-temporal-spatial-scale temporal convolution network for short-term load forecasting of power systems
10.1016/j.apenergy.2020.116328 · ExternalCitation · doi-reference
An adaptive ensemble framework with representative subset based weight correction for short-term forecast of peak power load
10.1016/j.apenergy.2022.120156 · ExternalCitation · doi-reference
Integrated approaches in resilient hierarchical load forecasting via TCN and optimal valley filling based demand response application
10.1016/j.apenergy.2024.122722 · ExternalCitation · doi-reference
A spatial multi-resolution multi-objective data-driven ensemble model for multi-step air quality index forecasting based on real-time decomposition
10.1016/j.compind.2020.103387 · ExternalCitation · doi-reference
Intelligent crude oil price probability forecasting: Deep learning models and industry applications
10.1016/j.compind.2024.104150 · ExternalCitation · doi-reference
Energy consumption forecasting in non-stationary machining processes based on a physics-guided transformer
10.1016/j.compind.2025.104321 · ExternalCitation · doi-reference
A novel interval-valued carbon price forecasting paradigm: multi-factor intelligent recognition-based ensemble learning
10.1016/j.compind.2025.104352 · ExternalCitation · doi-reference
Reliability evaluation of wind power systems by integrating granularity-related latin hypercube sampling with LSTM-based prediction
10.1016/j.compind.2025.104365 · ExternalCitation · doi-reference
An association rule-assisted multi-time-series forecasting method for non-production material consumption in the automotive sector
10.1016/j.compind.2025.104366 · ExternalCitation · doi-reference
Global electricity demand forecasting for multi-consumer retailers using a decomposition-based multi-sight convolutional neural network
10.1016/j.compind.2025.104415 · ExternalCitation · doi-reference
A short-term integrated wind speed prediction system based on fuzzy set feature extraction and intelligent optimization
10.1016/j.compind.2025.104418 · ExternalCitation · doi-reference
Electricity demand forecasting at distribution and household levels using explainable causal graph neural network
10.1016/j.egyai.2024.100368 · ExternalCitation · doi-reference
A short-term load forecasting model of multi-scale CNN-LSTM hybrid neural network considering the real-time electricity price
10.1016/j.egyr.2020.11.078 · ExternalCitation · doi-reference
Modeling and forecasting hourly electricity demand by SARIMAX with interactions
10.1016/j.energy.2018.09.157 · ExternalCitation · doi-reference
Graph convolutional network-based aggregated demand response baseline load estimation
10.1016/j.energy.2022.123847 · ExternalCitation · doi-reference
Short-term power load forecasting for combined heat and power using CNN-LSTM enhanced by attention mechanism
10.1016/j.energy.2023.128274 · ExternalCitation · doi-reference
Electrical load forecasting based on variable T-distribution and dual attention mechanism
10.1016/j.energy.2023.128569 · ExternalCitation · doi-reference
Review of load forecasting based on artificial intelligence methodologies, models, and challenges
10.1016/j.epsr.2022.108067 · ExternalCitation · doi-reference
Short-term load forecasting based on CEEMDAN and Transformer
10.1016/j.epsr.2022.108885 · ExternalCitation · doi-reference
Graph Convolutional Networks based short-term load forecasting: Leveraging spatial information for improved accuracy
10.1016/j.epsr.2024.110263 · ExternalCitation · doi-reference
A hybrid model for deep learning short-term power load forecasting based on feature extraction statistics techniques
10.1016/j.eswa.2023.122012 · ExternalCitation · doi-reference
A hybrid machine learning model for forecasting a billing period’s peak electric load days
10.1016/j.ijforecast.2019.03.025 · ExternalCitation · doi-reference
Forecasting day-ahead electricity prices with spatial dependence
10.1016/j.ijforecast.2023.11.006 · ExternalCitation · doi-reference
A review of short term load forecasting using artificial neural network models
10.1016/j.procs.2015.04.160 · ExternalCitation · doi-reference
Electrical load forecasting models: A critical systematic review
10.1016/j.scs.2017.08.009 · ExternalCitation · doi-reference
Power load forecasting based on spatial–temporal fusion graph convolution network
10.1016/j.techfore.2024.123435 · ExternalCitation · doi-reference
Forecasting water quality indices using generalized ridge model, regularized weighted kernel ridge model, and optimized multivariate variational mode decomposition
10.1038/s41598-025-99341-w · ExternalCitation · doi-reference
A hybrid method based on wavelet, ANN and ARIMA model for short-term load forecasting
10.1080/0952813x.2013.813976 · ExternalCitation · doi-reference
A comprehensive survey on graph neural networks
10.1109/tnnls.2020.2978386 · ExternalCitation · doi-reference
Deep learning for household load forecasting—A novel pooling deep RNN
10.1109/tsg.2017.2686012 · ExternalCitation · doi-reference
Short-term residential load forecasting based on LSTM recurrent neural network
10.1109/tsg.2017.2753802 · ExternalCitation · doi-reference
Spatial-temporal residential short-term load forecasting via graph neural networks
10.1109/tsg.2021.3093515 · ExternalCitation · doi-reference
A transformer-based method of multienergy load forecasting in integrated energy system
10.1109/tsg.2022.3166600 · ExternalCitation · doi-reference
Efficient residential electric load forecasting via transfer learning and graph neural networks
10.1109/tsg.2022.3208211 · ExternalCitation · doi-reference
A global modeling framework for load forecasting in distribution networks
10.1109/tsg.2023.3264525 · ExternalCitation · doi-reference
10.1145/3447548.3467430
10.1145/3447548.3467430 · ExternalCitation · doi-reference
Artificial neural network and SARIMA based models for power load forecasting in Turkish electricity market
10.1371/journal.pone.0175915 · ExternalCitation · doi-reference
Regression-SARIMA modelling of daily peak electricity demand in South Africa
10.17159/2413-3051/2012/v23i3a3169 · ExternalCitation · doi-reference
Methods and models for electric load forecasting: a comprehensive review
10.2478/jlst-2020-0004 · ExternalCitation · doi-reference
