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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:

Short-term electricity price forecasting based on similarity day screening, two-layer decomposition technique and Bi-LSTM neural network
Keke Wang, Min Yu, Dongxiao Niu, et al.
Applied Soft Computing (2023) Vol. 136, pp. 110018-110018
Closed Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

A multi-state fusion informer integrating transfer learning for metal tube bending early wrinkling prediction
Zili Wang, Yujun Yuan, Shuyou Zhang, et al.
Applied Soft Computing (2023) Vol. 151, pp. 110991-110991
Closed Access | Times Cited: 42
A new approach to seasonal energy consumption forecasting using temporal convolutional networks
Abdul Khalique Shaikh, Amril Nazir, Nadia Khalique, et al.
Results in Engineering (2023) Vol. 19, pp. 101296-101296
Open Access | Times Cited: 35
Structure Optimization of Ensemble Learning Methods and Seasonal Decomposition Approaches to Energy Price Forecasting in Latin America: A Case Study about Mexico
Anne Carolina Rodrigues Klaar, Stéfano Frizzo Stefenon, Laio Oriel Seman, et al.
Energies (2023) Vol. 16, Iss. 7, pp. 3184-3184
Open Access | Times Cited: 34
Two-step deep learning framework with error compensation technique for short-term, half-hourly electricity price forecasting
Sujan Ghimire, Ravinesh C. Deo, David Casillas-Pérez, et al.
Applied Energy (2023) Vol. 353, pp. 122059-122059
Open Access | Times Cited: 25
Electricity market price forecasting using ELM and Bootstrap analysis: A case study of the German and Finnish Day-Ahead markets
Stylianos Loizidis, Andreas Kyprianou, George E. Georghiou
Applied Energy (2024) Vol. 363, pp. 123058-123058
Open Access | Times Cited: 14
BO-STA-LSTM: Building energy prediction based on a Bayesian Optimized Spatial-Temporal Attention enhanced LSTM method
Guannan Li, Yong Wang, Chengliang Xu, et al.
Developments in the Built Environment (2024) Vol. 18, pp. 100465-100465
Open Access | Times Cited: 8
Integrated Multi-Head Self-Attention Transformer model for electricity demand prediction incorporating local climate variables
Sujan Ghimire, Thong Nguyen‐Huy, Mohanad S. AL‐Musaylh, et al.
Energy and AI (2023) Vol. 14, pp. 100302-100302
Open Access | Times Cited: 16
MSV-net: Multi-scale visual-inspired network for short-term electricity price forecasting
Han Wu, Yan Liang, Jiani Heng, et al.
Energy (2024) Vol. 291, pp. 130350-130350
Closed Access | Times Cited: 6
Enhanced Day-Ahead Electricity Price Forecasting Using a Convolutional Neural Network–Long Short-Term Memory Ensemble Learning Approach with Multimodal Data Integration
Ziyang Wang, Masahiro Mae, Takeshi Yamane, et al.
Energies (2024) Vol. 17, Iss. 11, pp. 2687-2687
Open Access | Times Cited: 6
Interpretable short-term carbon dioxide emissions forecasting based on flexible two-stage decomposition and temporal fusion transformers
Binrong Wu, Huanze Zeng, Zhongrui Wang, et al.
Applied Soft Computing (2024) Vol. 159, pp. 111639-111639
Closed Access | Times Cited: 4
Enhanced Load Forecasting for Distributed Multi-Energy System: A Stacking Ensemble Learning Method With Deep Reinforcement Learning And Model Fusion
Xiaoxiao Ren, Xin Tian, Kai Wang, et al.
(2025)
Closed Access
Forecasting Crude Oil Prices: Evidence From WOA-VMD-FE-Transformer Model
Yu Liang, Xi Zhang, Yu Lin, et al.
Computational Economics (2025)
Closed Access
A hybrid system with optimized decomposition on random deep learning model for crude oil futures forecasting
Jie Wang, Ying Zhang
Expert Systems with Applications (2025), pp. 126706-126706
Closed Access
Enhanced load forecasting for distributed multi-energy system: A stacking ensemble learning method with deep reinforcement learning and model fusion
Xiaoxiao Ren, Xin Tian, Kai Wang, et al.
Energy (2025), pp. 135031-135031
Closed Access
Prediction of Ultra-Short Term Electricity Price Interval in Electricity Market Based on MIC-LSSVM-ABKDE
Fei He, Shuaibo Zhang
Lecture notes in electrical engineering (2025), pp. 219-229
Closed Access
Self-Adaptive Clustering Model Based on Variable Time-Series Similarity Measure Analysis for V2G Electricity Price Prediction
Tie Hua Zhou, Xirao Xun, Ling Wang, et al.
Applied Sciences (2025) Vol. 15, Iss. 4, pp. 2069-2069
Open Access
Dynamic energy cost prediction for industrial and commercial buildings using advanced Machine Learning and multi-pricing models
Qazi Waqas Khan, Anam Nawaz Khan, Bibi Misbah, et al.
Journal of Building Engineering (2025), pp. 112055-112055
Open Access
China’s Energy Stock Price Index Prediction Based on VECM–BiLSTM Model
Bingchun Liu, Zhang Xia, Yuan Gao, et al.
Energies (2025) Vol. 18, Iss. 5, pp. 1242-1242
Open Access
Short-Term Forecasting of Electricity Price using Ensemble Deep. Kernel Based Random Vector Functional Link Network
Someswari Perla, Ranjeeta Bisoi, P.K. Dash, et al.
Applied Soft Computing (2025), pp. 113012-113012
Closed Access
Comparative Study of Data-Driven Short-Term Forecasting Techniques in Electricity Price Prediction
Rahul Sagwal, S. N. Singh, J. Ramkumar, et al.
Lecture notes in networks and systems (2025), pp. 215-232
Closed Access
Optimal control and energy efficiency evaluation of district ice storage system
Hui Cao, Jiajing Lin, Nan Li
Energy (2023) Vol. 276, pp. 127598-127598
Closed Access | Times Cited: 12
Intraday Electricity Price Forecasting via LSTM and Trading Strategy for the Power Market: A Case Study of the West Denmark DK1 Grid Region
Deniz Kenan Kılıç, Peter Nielsen, Amila Thibbotuwawa
Energies (2024) Vol. 17, Iss. 12, pp. 2909-2909
Open Access | Times Cited: 3
Short-term load forecasting method of IES based on RLA neural network with dual signal processing
You Lv, Yijun Shi, Zeyang Li, et al.
Energy and Buildings (2024) Vol. 309, pp. 114074-114074
Closed Access | Times Cited: 2
A Two-Stage Forecasting Approach for Day-Ahead Electricity Price Based on Improved Wavelet Neural Network With ELM Initialization
Ziyu Qu, He Li, Xinxin Ge, et al.
IEEE Transactions on Industry Applications (2024) Vol. 60, Iss. 3, pp. 5061-5073
Closed Access | Times Cited: 1
Day-ahead electricity price prediction in multi-price zones based on multi-view fusion spatio-temporal graph neural network
Anbo Meng, Jianbin Zhu, Yan Baiping, et al.
Applied Energy (2024) Vol. 369, pp. 123553-123553
Closed Access | Times Cited: 1
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