Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Stacking Ensemble Methodology Using Deep Learning and ARIMA Models for Short-Term Load Forecasting
Pedro Bento, José Pombo, M.R.A. Calado, et al.
Energies (2021) Vol. 14, Iss. 21, pp. 7378-7378
Open Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

A comprehensive review on deep learning approaches for short-term load forecasting
Yavuz Eren, İbrahim Beklan Küçükdemiral
Renewable and Sustainable Energy Reviews (2023) Vol. 189, pp. 114031-114031
Open Access | Times Cited: 61
A deep model for short-term load forecasting applying a stacked autoencoder based on LSTM supported by a multi-stage attention mechanism
Zahra Fazlipour, Elaheh Mashhour, Mahmood Joorabian
Applied Energy (2022) Vol. 327, pp. 120063-120063
Closed Access | Times Cited: 57
PSO-Stacking improved ensemble model for campus building energy consumption forecasting based on priority feature selection
Yisheng Cao, Gang Liu, Jianping Sun, et al.
Journal of Building Engineering (2023) Vol. 72, pp. 106589-106589
Closed Access | Times Cited: 32
Highly fluctuating short-term load forecasting based on improved secondary decomposition and optimized VMD
Yan Wen, Su Pan, Xinxin Li, et al.
Sustainable Energy Grids and Networks (2024) Vol. 37, pp. 101270-101270
Closed Access | Times Cited: 11
Short-Term Load Forecasting Based on Optimized Random Forest and Optimal Feature Selection
Bianca Magalhães, Pedro Bento, José Pombo, et al.
Energies (2024) Vol. 17, Iss. 8, pp. 1926-1926
Open Access | Times Cited: 8
Performance decay prediction model of proton exchange membrane fuel cell based on particle swarm optimization and gate recurrent unit
Ziliang Zhao, Yifan Fu, Ji Pu, et al.
Energy and AI (2024) Vol. 17, pp. 100399-100399
Open Access | Times Cited: 5
Spatiotemporal characteristics and dynamic prediction of agricultural carbon compensation potential in the middle and lower reaches of the Yellow River Basin
Jikang Luo, Zhao Zhen, Jing Pang
Environmental Science and Pollution Research (2025)
Closed Access
Forecasting Daily Electricity Consumption in Thailand Using Regression, Artificial Neural Network, Support Vector Machine, and Hybrid Models
Warut Pannakkong, Thanyaporn Harncharnchai, Jirachai Buddhakulsomsiri
Energies (2022) Vol. 15, Iss. 9, pp. 3105-3105
Open Access | Times Cited: 21
A novel ensemble algorithm based on hydrological event diversity for urban rainfall–runoff model calibration and validation
Everett Snieder, Usman T. Khan
Journal of Hydrology (2023) Vol. 619, pp. 129193-129193
Closed Access | Times Cited: 11
A Random Forest-Convolutional Neural Network Deep Learning Model for Predicting the Wholesale Price Index of Potato in India
Soumik Ray, Tufleuddin Biswas, Walid Emam, et al.
Potato Research (2024)
Closed Access | Times Cited: 3
Prediction maintenance based on vibration analysis and deep learning — A case study of a drying press supported on a Hidden Markov Model
Alexandre Martins, Inácio Fonseca, José Torres Farinha, et al.
Applied Soft Computing (2024) Vol. 163, pp. 111885-111885
Open Access | Times Cited: 3
Predicting Thermoelectric Power Plants Diesel/Heavy Fuel Oil Engine Fuel Consumption Using Univariate Forecasting and XGBoost Machine Learning Models
Elias Amancio Siqueira-Filho, Maira Farias Andrade Lira, Attílio Converti, et al.
Energies (2023) Vol. 16, Iss. 7, pp. 2942-2942
Open Access | Times Cited: 7
Multivariate and hybrid data-driven models to predict thermoelectric power plants fuel consumption
Elias Amancio Siqueira-Filho, Maira Farias Andrade Lira, Hugo Valadares Siqueira, et al.
Expert Systems with Applications (2024) Vol. 252, pp. 124219-124219
Closed Access | Times Cited: 2
Advancements in Household Load Forecasting: Deep Learning Model with Hyperparameter Optimization
Hamdi A. Al-Jamimi, Galal M. BinMakhashen, Muhammed Y. Worku, et al.
Electronics (2023) Vol. 12, Iss. 24, pp. 4909-4909
Open Access | Times Cited: 6
An office building energy consumption forecasting model with dynamically combined residual error correction based on the optimal model
Zengxi Feng, Maoqiang Zhang, Na Wei, et al.
Energy Reports (2022) Vol. 8, pp. 12442-12455
Open Access | Times Cited: 10
Short-Term Load Forecasting Based on Outlier Correction, Decomposition, and Ensemble Reinforcement Learning
Jiakang Wang, Hui Liu, Guangji Zheng, et al.
Energies (2023) Vol. 16, Iss. 11, pp. 4401-4401
Open Access | Times Cited: 4
Short-Term Electricity Load Forecasting Based on NeuralProphet and CNN-LSTM
Shuai Lu, Taotao Bao
IEEE Access (2024) Vol. 12, pp. 76870-76879
Open Access | Times Cited: 1
Short-term Load Forecasting using the Combined Method of Wavelet Transform and Neural Networks Tuned by the Gray Wolf Optimization Algorithm
S. Mohammadali Zanjani, Hossein Shahinzadeh, Jalal Moradi, et al.
(2022), pp. 294-299
Closed Access | Times Cited: 6
A Group Resident Daily Load Forecasting Method Fusing Self-Attention Mechanism Based on Load Clustering
Jie Cao, Ru-Xuan Zhang, Chao-Qiang Liu, et al.
Applied Sciences (2023) Vol. 13, Iss. 2, pp. 1165-1165
Open Access | Times Cited: 3
A Stochastic Load Forecasting Approach to Prevent Transformer Failures and Power Quality Issues Amid the Evolving Electrical Demands Facing Utilities
John O’Donnell, Wencong Su
Energies (2023) Vol. 16, Iss. 21, pp. 7251-7251
Open Access | Times Cited: 2
An Overview Of The Latest Machine Learning Trends In Short-Term Load Forecasting
Pedro Bento, José Pombo, S.J.P.S. Mariano, et al.
2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) (2022), pp. 1-8
Closed Access | Times Cited: 3
Residential Electricity Consumption Prediction Method Based on Deep Learning and Federated Learning Under Cloud Edge Collaboration Architecture
Wei Wang, Xiaotian Wang, Xiaotian Ma, et al.
International Journal of Gaming and Computer-Mediated Simulations (2024) Vol. 16, Iss. 1, pp. 1-19
Open Access
Hybrid attention-based improved temporal convolutional BiGRU approach for short-term load forecasting
Yu Xie, Pan Zeng, Jiakun Chen
Journal of Physics Conference Series (2024) Vol. 2703, Iss. 1, pp. 012052-012052
Open Access
Comparative Analysis of Machine Learning Models for Crop Yield Prediction in the Telangana Region
Sowmya Padam
(2024)
Closed Access
Performance Decay Prediction Model of Proton Exchange Membrane Fuel Cell Based on Particle Swarm Optimization and Gate Recurrent Unit (基于粒子群优化和栅极循环单元的质子交换膜燃料电池性能衰减预测模型)
Ziliang Zhao, Yifan Fu, Ji Pu, et al.
(2024)
Closed Access
Page 1 - Next Page

Scroll to top