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:

Modelling a combined method based on ANFIS and neural network improved by DE algorithm: A case study for short-term electricity demand forecasting
Yi Yang, Yanhua Chen, Yachen Wang, et al.
Applied Soft Computing (2016) Vol. 49, pp. 663-675
Closed Access | Times Cited: 148

Showing 1-25 of 148 citing articles:

An optimized model using LSTM network for demand forecasting
Hossein Abbasimehr, Mostafa Shabani, Mohsen Yousefi
Computers & Industrial Engineering (2020) Vol. 143, pp. 106435-106435
Closed Access | Times Cited: 389
A review on renewable energy and electricity requirement forecasting models for smart grid and buildings
Tanveer Ahmad, Hongcai Zhang, Biao Yan
Sustainable Cities and Society (2020) Vol. 55, pp. 102052-102052
Closed Access | Times Cited: 368
A combined model based on CEEMDAN and modified flower pollination algorithm for wind speed forecasting
Wenyu Zhang, Zongxi Qu, Kequan Zhang, et al.
Energy Conversion and Management (2017) Vol. 136, pp. 439-451
Closed Access | Times Cited: 336
A deep learning framework for building energy consumption forecast
Nivethitha Somu, M. R. Gauthama Raman, Krithi Ramamritham
Renewable and Sustainable Energy Reviews (2020) Vol. 137, pp. 110591-110591
Closed Access | Times Cited: 331
Forecasting methods in energy planning models
Kumar Biswajit Debnath, Monjur Mourshed
Renewable and Sustainable Energy Reviews (2018) Vol. 88, pp. 297-325
Open Access | Times Cited: 293
A Two-Layer Nonlinear Combination Method for Short-Term Wind Speed Prediction Based on ELM, ENN, and LSTM
Min-Rong Chen, Guo‐Qiang Zeng, Kang‐Di Lu, et al.
IEEE Internet of Things Journal (2019) Vol. 6, Iss. 4, pp. 6997-7010
Closed Access | Times Cited: 218
Conventional models and artificial intelligence-based models for energy consumption forecasting: A review
Nan Wei, Changjun Li, Xiaomei Peng, et al.
Journal of Petroleum Science and Engineering (2019) Vol. 181, pp. 106187-106187
Closed Access | Times Cited: 203
Hybrid structures in time series modeling and forecasting: A review
Zahra Hajirahimi, Mehdi Khashei
Engineering Applications of Artificial Intelligence (2019) Vol. 86, pp. 83-106
Closed Access | Times Cited: 184
Gross electricity consumption forecasting using LSTM and SARIMA approaches: A case study of Türkiye
Mehmet Bilgili, Engin Pınar
Energy (2023) Vol. 284, pp. 128575-128575
Closed Access | Times Cited: 45
Research and application of a combined model based on variable weight for short term wind speed forecasting
Hongmin Li, Jianzhou Wang, Haiyan Lu, et al.
Renewable Energy (2017) Vol. 116, pp. 669-684
Open Access | Times Cited: 140
Forecasting energy demand, wind generation and carbon dioxide emissions in Ireland using evolutionary neural networks
Karl Mason, Jim Duggan, Enda Howley
Energy (2018) Vol. 155, pp. 705-720
Closed Access | Times Cited: 128
Forecasting energy consumption and wind power generation using deep echo state network
Huanling Hu, Lin Wang, Sheng-Xiang Lv
Renewable Energy (2020) Vol. 154, pp. 598-613
Closed Access | Times Cited: 126
A novel composite electricity demand forecasting framework by data processing and optimized support vector machine
Ping Jiang, Ranran Li, Ningning Liu, et al.
Applied Energy (2020) Vol. 260, pp. 114243-114243
Closed Access | Times Cited: 114
A state-of-the-art review of artificial intelligence techniques for short-term electric load forecasting
Kasım Zor, Oğuzhan Timur, Ahmet Teke
(2017), pp. 1-7
Closed Access | Times Cited: 105
Variable weights combined model based on multi-objective optimization for short-term wind speed forecasting
Ping Jiang, Zhenkun Liu
Applied Soft Computing (2019) Vol. 82, pp. 105587-105587
Closed Access | Times Cited: 98
Mixed kernel based extreme learning machine for electric load forecasting
Yanhua Chen, Marius Kloft, Yi Yang, et al.
Neurocomputing (2018) Vol. 312, pp. 90-106
Closed Access | Times Cited: 97
A Systematic Review of Statistical and Machine Learning Methods for Electrical Power Forecasting with Reported MAPE Score
Eliana Vivas, Héctor Allende‐Cid, Rodrigo Salas
Entropy (2020) Vol. 22, Iss. 12, pp. 1412-1412
Open Access | Times Cited: 97
A novel decomposition‐ensemble model for forecasting short‐term load‐time series with multiple seasonal patterns
Xiaobo Zhang, Jianzhou Wang
Applied Soft Computing (2018) Vol. 65, pp. 478-494
Closed Access | Times Cited: 92
An integrated approach based on artificial intelligence and novel meta-heuristic algorithms to predict demand for dairy products: a case study
Alireza Goli, Hasan Khademi-Zare, Reza Tavakkoli‐Moghaddam, et al.
Network Computation in Neural Systems (2021) Vol. 32, Iss. 1, pp. 1-35
Closed Access | Times Cited: 92
An interval decomposition-ensemble approach with data-characteristic-driven reconstruction for short-term load forecasting
Dongchuan Yang, Ju’e Guo, Shaolong Sun, et al.
Applied Energy (2021) Vol. 306, pp. 117992-117992
Closed Access | Times Cited: 74
Modeling and Forecasting Electricity Demand and Prices: A Comparison of Alternative Approaches
Ismail Shah, Hasnain Iftikhar, Sajid Ali
Journal of Mathematics (2022) Vol. 2022, Iss. 1
Open Access | Times Cited: 44
A Comprehensive Survey on Load Forecasting Hybrid Models: Navigating the Futuristic Demand Response Patterns through Experts and Intelligent Systems
Kinza Fida, Usman Abbasi, Muhammad Adnan, et al.
Results in Engineering (2024) Vol. 23, pp. 102773-102773
Open Access | Times Cited: 7
A novel combined model based on echo state network for multi-step ahead wind speed forecasting: A case study of NREL
Yanhua Chen, Zhaoshuang He, Zhihao Shang, et al.
Energy Conversion and Management (2018) Vol. 179, pp. 13-29
Closed Access | Times Cited: 74
Research and application of ensemble forecasting based on a novel multi-objective optimization algorithm for wind-speed forecasting
Zongxi Qu, Kequan Zhang, Wenqian Mao, et al.
Energy Conversion and Management (2017) Vol. 154, pp. 440-454
Closed Access | Times Cited: 66
A novel hybrid forecasting scheme for electricity demand time series
Ranran Li, Ping Jiang, Hufang Yang, et al.
Sustainable Cities and Society (2020) Vol. 55, pp. 102036-102036
Closed Access | Times Cited: 65
Page 1 - Next Page

Scroll to top