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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:

Combined forecasting models for wind energy forecasting: A case study in China
Ling Xiao, Jianzhou Wang, Yao Dong, et al.
Renewable and Sustainable Energy Reviews (2015) Vol. 44, pp. 271-288
Closed Access | Times Cited: 180

Showing 26-50 of 180 citing articles:

A novel combination forecasting model for wind power integrating least square support vector machine, deep belief network, singular spectrum analysis and locality-sensitive hashing
Yachao Zhang, Jian Le, Xiaobing Liao, et al.
Energy (2018) Vol. 168, pp. 558-572
Closed Access | Times Cited: 110
Long-Term Wind Power Forecasting Using Tree-Based Learning Algorithms
Amirhossein Ahmadi, Mojtaba Nabipour, Behnam Mohammadi‐Ivatloo, et al.
IEEE Access (2020) Vol. 8, pp. 151511-151522
Open Access | Times Cited: 105
Short-term wind power combined forecasting based on error forecast correction
Zhengtang Liang, Jun Liang, Chengfu Wang, et al.
Energy Conversion and Management (2016) Vol. 119, pp. 215-226
Closed Access | Times Cited: 104
Multi-objective data-ensemble wind speed forecasting model with stacked sparse autoencoder and adaptive decomposition-based error correction
Hui Liu, Chao Chen
Applied Energy (2019) Vol. 254, pp. 113686-113686
Closed Access | Times Cited: 100
A novel forecasting model based on a hybrid processing strategy and an optimized local linear fuzzy neural network to make wind power forecasting: A case study of wind farms in China
Qingli Dong, Yuhuan Sun, Peizhi Li
Renewable Energy (2016) Vol. 102, pp. 241-257
Closed Access | Times Cited: 94
A hybrid forecasting approach applied in wind speed forecasting based on a data processing strategy and an optimized artificial intelligence algorithm
Zhongshan Yang, Wang Jian
Energy (2018) Vol. 160, pp. 87-100
Closed Access | Times Cited: 89
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
Critical Review of Data, Models and Performance Metrics for Wind and Solar Power Forecast
V. Prema, Mahajan Sagar Bhaskar, Dhafer Almakhles, et al.
IEEE Access (2021) Vol. 10, pp. 667-688
Open Access | Times Cited: 81
Design of a combined wind speed forecasting system based on decomposition-ensemble and multi-objective optimization approach
Liangqing Luo, Hongmin Li, Jianzhou Wang, et al.
Applied Mathematical Modelling (2020) Vol. 89, pp. 49-72
Closed Access | Times Cited: 79
Dynamic ensemble wind speed prediction model based on hybrid deep reinforcement learning
Chao Chen, Hui Liu
Advanced Engineering Informatics (2021) Vol. 48, pp. 101290-101290
Closed Access | Times Cited: 63
Multimodal Data Guided Spatial Feature Fusion and Grouping Strategy for E-Commerce Commodity Demand Forecasting
Weiwei Cai, Yaping Song, Zhanguo Wei
Mobile Information Systems (2021) Vol. 2021, pp. 1-14
Open Access | Times Cited: 58
Combined Approach for Short-Term Wind Power Forecasting Based on Wave Division and Seq2Seq Model Using Deep Learning
Lin Ye, Binhua Dai, Ming Pei, et al.
IEEE Transactions on Industry Applications (2022) Vol. 58, Iss. 2, pp. 2586-2596
Closed Access | Times Cited: 49
Short-term load forecasting with an improved dynamic decomposition-reconstruction-ensemble approach
Dongchuan Yang, Ju’e Guo, Yanzhao Li, et al.
Energy (2022) Vol. 263, pp. 125609-125609
Closed Access | Times Cited: 37
Evolving long short-term memory neural network for wind speed forecasting
Cong Huang, Hamid Reza Karimi, Peng Mei, et al.
Information Sciences (2023) Vol. 632, pp. 390-410
Open Access | Times Cited: 30
Estimating the output power and wind speed with ML methods: A case study in Texas
Seyed Matin Malakouti
Case Studies in Chemical and Environmental Engineering (2023) Vol. 7, pp. 100324-100324
Open Access | Times Cited: 28
An overview of medium- to long-term predictions of global wave energy resources
Chongwei Zheng, Qing Wang, Chong Yin Li
Renewable and Sustainable Energy Reviews (2017) Vol. 79, pp. 1492-1502
Closed Access | Times Cited: 83
Analysis and forecasting of the oil consumption in China based on combination models optimized by artificial intelligence algorithms
LI Jing-rui, Rui Wang, Jianzhou Wang, et al.
Energy (2017) Vol. 144, pp. 243-264
Closed Access | Times Cited: 69
Comprehensive evaluation index system for wind power utilization levels in wind farms in China
Ruijing Shi, Xiaochao Fan, Ying He
Renewable and Sustainable Energy Reviews (2016) Vol. 69, pp. 461-471
Closed Access | Times Cited: 67
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
Forecasting China's total energy demand and its structure using ADL-MIDAS model
Yongda He, Boqiang Lin
Energy (2018) Vol. 151, pp. 420-429
Open Access | Times Cited: 66
Combined model with secondary decomposition-model selection and sample selection for multi-step wind power forecasting
Zhuochun Wu, Xiangjie Xia, Li‐Ye Xiao, et al.
Applied Energy (2019) Vol. 261, pp. 114345-114345
Closed Access | Times Cited: 66
A combination forecasting approach applied in multistep wind speed forecasting based on a data processing strategy and an optimized artificial intelligence algorithm
Zhongshan Yang, Wang Jian
Applied Energy (2018) Vol. 230, pp. 1108-1125
Closed Access | Times Cited: 65
A novel system based on neural networks with linear combination framework for wind speed forecasting
Jianzhou Wang, Na Zhang, Haiyan Lu
Energy Conversion and Management (2018) Vol. 181, pp. 425-442
Closed Access | Times Cited: 65
Research and application of a combined model based on multi-objective optimization for electrical load forecasting
Li‐Ye Xiao, Wei Shao, Mengxia Yu, et al.
Energy (2016) Vol. 119, pp. 1057-1074
Closed Access | Times Cited: 62
Short-Term Wind Speed Forecasting Based on Information of Neighboring Wind Farms
Zhongju Wang, Jing Zhang, Zhang Yu, et al.
IEEE Access (2020) Vol. 8, pp. 16760-16770
Open Access | Times Cited: 57

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