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OpenAlex Citation Counts

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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:

An optimized grey model for annual power load forecasting
Huiru Zhao, Sen Guo
Energy (2016) Vol. 107, pp. 272-286
Closed Access | Times Cited: 201

Showing 26-50 of 201 citing articles:

Using a self-adaptive grey fractional weighted model to forecast Jiangsu’s electricity consumption in China
Xiaoyue Zhu, Yaoguo Dang, Song Ding
Energy (2019) Vol. 190, pp. 116417-116417
Closed Access | Times Cited: 90
Forecasting the industrial solar energy consumption using a novel seasonal GM(1,1) model with dynamic seasonal adjustment factors
Zheng‐Xin Wang, Zhiwei Wang, Qin Li
Energy (2020) Vol. 200, pp. 117460-117460
Closed Access | Times Cited: 90
A novel self-adapting intelligent grey model for forecasting China's natural-gas demand
Song Ding
Energy (2018) Vol. 162, pp. 393-407
Closed Access | Times Cited: 89
China's dependency on foreign oil will exceed 80% by 2030: Developing a novel NMGM-ARIMA to forecast China's foreign oil dependence from two dimensions
Qiang Wang, Shuyu Li, Rongrong Li
Energy (2018) Vol. 163, pp. 151-167
Closed Access | Times Cited: 88
Short-Term Power Load Forecasting Method Based on Improved Exponential Smoothing Grey Model
Jianwei Mi, Libin Fan, Xuechao Duan, et al.
Mathematical Problems in Engineering (2018) Vol. 2018, pp. 1-11
Open Access | Times Cited: 87
A Robust Prognostic Indicator for Renewable Energy Technologies: A Novel Error Correction Grey Prediction Model
Daming Zhou, Ahmed Al‐Durra, Ke Zhang, et al.
IEEE Transactions on Industrial Electronics (2019) Vol. 66, Iss. 12, pp. 9312-9325
Closed Access | Times Cited: 87
A novel hybrid model based on combined preprocessing method and advanced optimization algorithm for power load forecasting
Ying Nie, Ping Jiang, Haipeng Zhang
Applied Soft Computing (2020) Vol. 97, pp. 106809-106809
Closed Access | Times Cited: 82
Short-term electrical load forecasting based on error correction using dynamic mode decomposition
Xiangyu Kong, Chuang Li, Chengshan Wang, et al.
Applied Energy (2019) Vol. 261, pp. 114368-114368
Closed Access | Times Cited: 75
Forecasting electricity consumption using a novel hybrid model
Guo‐Feng Fan, Xiao Wei, Yating Li, et al.
Sustainable Cities and Society (2020) Vol. 61, pp. 102320-102320
Closed Access | Times Cited: 75
Improving the Bi-LSTM model with XGBoost and attention mechanism: A combined approach for short-term power load prediction
Yeming Dai, Qiong Zhou, Mingming Leng, et al.
Applied Soft Computing (2022) Vol. 130, pp. 109632-109632
Closed Access | Times Cited: 64
Transformer-Based Model for Electrical Load Forecasting
Alexandra L’Heureux, Katarina Grolinger, Miriam A. M. Capretz
Energies (2022) Vol. 15, Iss. 14, pp. 4993-4993
Open Access | Times Cited: 61
A hybrid optimized grey seasonal variation index model improved by whale optimization algorithm for forecasting the residential electricity consumption
Xin Xiong, Xi Hu, Huan Guo
Energy (2021) Vol. 234, pp. 121127-121127
Closed Access | Times Cited: 56
A novel two-stage seasonal grey model for residential electricity consumption forecasting
Pei Du, Ju’e Guo, Shaolong Sun, et al.
Energy (2022) Vol. 258, pp. 124664-124664
Closed Access | Times Cited: 39
Evaluating and forecasting the niche fitness of regional innovation ecosystems: A comparative evaluation of different optimized grey models
Xuemei Xie, Xiaojie Liu, Cristina Blanco González‐Tejero
Technological Forecasting and Social Change (2023) Vol. 191, pp. 122473-122473
Closed Access | Times Cited: 27
A novel structure adaptive fractional derivative grey model and its application in energy consumption prediction
Yong Wang, Lang Sun, Rui Yang, et al.
Energy (2023) Vol. 282, pp. 128380-128380
Closed Access | Times Cited: 23
Short-term load forecasting method based on secondary decomposition and improved hierarchical clustering
Wenting Zha, Yongqiang Ji, Liang Chen
Results in Engineering (2024) Vol. 22, pp. 101993-101993
Open Access | Times Cited: 13
Urban long term electricity demand forecast method based on system dynamics of the new economic normal: The case of Tianjin
Yongxiu He, Jie Jiao, Qian Chen, et al.
Energy (2017) Vol. 133, pp. 9-22
Closed Access | Times Cited: 71
A hybrid forecasting approach applied in the electrical power system based on data preprocessing, optimization and artificial intelligence algorithms
Ping Jiang, Xuejiao Ma
Applied Mathematical Modelling (2016) Vol. 40, Iss. 23-24, pp. 10631-10649
Open Access | Times Cited: 70
Forecasting annual electricity consumption in China by employing a conformable fractional grey model in opposite direction
Wanli Xie, Wen-Ze Wu, Chong Liu, et al.
Energy (2020) Vol. 202, pp. 117682-117682
Closed Access | Times Cited: 68
Forecasting China's oil consumption: A comparison of novel nonlinear-dynamic grey model (GM), linear GM, nonlinear GM and metabolism GM
Qiang Wang, Xiaoxin Song
Energy (2019) Vol. 183, pp. 160-171
Closed Access | Times Cited: 65
Forecasting the non-renewable energy consumption by an adjacent accumulation grey model
Hongying Zhao, Lifeng Wu
Journal of Cleaner Production (2020) Vol. 275, pp. 124113-124113
Closed Access | Times Cited: 65
Multifractional Brownian motion and quantum-behaved particle swarm optimization for short term power load forecasting: An integrated approach
Wanqing Song, Carlo Cattani, Chi‐Hung Chi
Energy (2020) Vol. 194, pp. 116847-116847
Closed Access | Times Cited: 64
Wind Power Prediction Based on LS-SVM Model with Error Correction
Yagang Zhang, Pengyu Wang, Tongguang Ni, et al.
Advances in Electrical and Computer Engineering (2017) Vol. 17, Iss. 1, pp. 3-8
Open Access | Times Cited: 62
A new hybrid model to predict the electrical load in five states of Australia
Jinran Wu, Zhesen Cui, Yanyan Chen, et al.
Energy (2018) Vol. 166, pp. 598-609
Open Access | Times Cited: 61
Integrating linear and nonlinear forecasting techniques based on grey theory and artificial intelligence to forecast shale gas monthly production in Pennsylvania and Texas of the United States
Qiang Wang, Feng Jiang
Energy (2019) Vol. 178, pp. 781-803
Closed Access | Times Cited: 57

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