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:

Short-term wind speed prediction based on improved PSO algorithm optimized EM-ELM
Zhongda Tian, Yi Ren, Gang Wang
Energy Sources Part A Recovery Utilization and Environmental Effects (2018) Vol. 41, Iss. 1, pp. 26-46
Closed Access | Times Cited: 76

Showing 1-25 of 76 citing articles:

Short-term wind speed forecasting based on the Jaya-SVM model
Mingshuai Liu, Zheming Cao, Jing Zhang, et al.
International Journal of Electrical Power & Energy Systems (2020) Vol. 121, pp. 106056-106056
Closed Access | Times Cited: 176

Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization
Rana Muhammad Adnan, Reham R. Mostafa, Özgür Kişi, et al.
Knowledge-Based Systems (2021) Vol. 230, pp. 107379-107379
Closed Access | Times Cited: 165

Short-term wind speed prediction based on LMD and improved FA optimized combined kernel function LSSVM
Zhongda Tian
Engineering Applications of Artificial Intelligence (2020) Vol. 91, pp. 103573-103573
Closed Access | Times Cited: 159

Groundwater level prediction using an improved ELM model integrated with hybrid particle swarm optimisation and grey wolf optimisation
Sandeep Samantaray, Abinash Sahoo
Groundwater for Sustainable Development (2024) Vol. 26, pp. 101178-101178
Closed Access | Times Cited: 21

A review of applications of artificial intelligent algorithms in wind farms
Yirui Wang, Yang Yu, Shuyang Cao, et al.
Artificial Intelligence Review (2019) Vol. 53, Iss. 5, pp. 3447-3500
Closed Access | Times Cited: 106

A prediction approach using ensemble empirical mode decomposition‐permutation entropy and regularized extreme learning machine for short‐term wind speed
Zhongda Tian, Shujiang Li, Yanhong Wang
Wind Energy (2019) Vol. 23, Iss. 2, pp. 177-206
Closed Access | Times Cited: 97

Short-term wind speed forecasting approach using Ensemble Empirical Mode Decomposition and Deep Boltzmann Machine
Santhosh Madasthu, Chintham Venkaiah, D. M. Vinod Kumar
Sustainable Energy Grids and Networks (2019) Vol. 19, pp. 100242-100242
Closed Access | Times Cited: 92

Modes decomposition forecasting approach for ultra-short-term wind speed
Zhongda Tian
Applied Soft Computing (2021) Vol. 105, pp. 107303-107303
Closed Access | Times Cited: 77

A combination forecasting model of wind speed based on decomposition
Zhongda Tian, Hao Li, Feihong Li
Energy Reports (2021) Vol. 7, pp. 1217-1233
Open Access | Times Cited: 77

Artificial Neural Networks Hidden Unit and Weight Connection Optimization by Quasi-Refection-Based Learning Artificial Bee Colony Algorithm
Nebojša Bačanin, Timea Bezdan, K. Venkatachalam, et al.
IEEE Access (2021) Vol. 9, pp. 169135-169155
Open Access | Times Cited: 72

Hybrid intelligent framework for carbon price prediction using improved variational mode decomposition and optimal extreme learning machine
Jujie Wang, Quan Cui, Maolin He
Chaos Solitons & Fractals (2022) Vol. 156, pp. 111783-111783
Closed Access | Times Cited: 47

Short term wind speed prediction based on CEESMDAN and improved seagull optimization kernel extreme learning machine
Xiwen Qin, Liping Yuan, Xiaogang Dong, et al.
Earth Science Informatics (2025) Vol. 18, Iss. 1
Closed Access | Times Cited: 1

Backtracking search optimization algorithm-based least square support vector machine and its applications
Zhongda Tian
Engineering Applications of Artificial Intelligence (2020) Vol. 94, pp. 103801-103801
Closed Access | Times Cited: 54

Optimization scheme of wind energy prediction based on artificial intelligence
Yagang Zhang, Ruixuan Li, Jinghui Zhang
Environmental Science and Pollution Research (2021) Vol. 28, Iss. 29, pp. 39966-39981
Closed Access | Times Cited: 46

An adaptive hybrid system using deep learning for wind speed forecasting
Paulo S. G. de Mattos Neto, João Fausto Lorenzato de Oliveira, Domingos S. de O. Santos, et al.
Information Sciences (2021) Vol. 581, pp. 495-514
Closed Access | Times Cited: 42

A point-interval wind speed forecasting system based on fuzzy theory and neural networks architecture searching strategy
Jingjiang Liu, Jianzhou Wang, Yunbo Niu, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 132, pp. 107906-107906
Closed Access | Times Cited: 6

Wind source potential assessment using Sentinel 1 satellite and a new forecasting model based on machine learning: A case study Sardinia islands
Meysam Majidi Nezhad, Azim Heydari, Daniele Groppi, et al.
Renewable Energy (2020) Vol. 155, pp. 212-224
Closed Access | Times Cited: 40

A novel hybrid model for short-term prediction of wind speed
Haize Hu, Yunyi Li, Xiangping Zhang, et al.
Pattern Recognition (2022) Vol. 127, pp. 108623-108623
Closed Access | Times Cited: 26

A digital twin dosing system for iron reverse flotation
Dingsen Zhang, Xianwen Gao
Journal of Manufacturing Systems (2022) Vol. 63, pp. 238-249
Closed Access | Times Cited: 25

Particle Swarm Optimization-Based Noise Filtering Algorithm for Photon Cloud Data in Forest Area
Jiapeng Huang, Yanqiu Xing, Haotian You, et al.
Remote Sensing (2019) Vol. 11, Iss. 8, pp. 980-980
Open Access | Times Cited: 41

Network traffic prediction method based on wavelet transform and multiple models fusion
Zhongda Tian
International Journal of Communication Systems (2020) Vol. 33, Iss. 11
Closed Access | Times Cited: 37

Preliminary Research of Chaotic Characteristics and Prediction of Short-Term Wind Speed Time Series
Zhongda Tian
International Journal of Bifurcation and Chaos (2020) Vol. 30, Iss. 12, pp. 2050176-2050176
Closed Access | Times Cited: 36

An extreme learning machine based very short-term wind power forecasting method for complex terrain
Hakan Açıkgöz, Ceyhun Yıldız, Mustafa ŞEKKELİ
Energy Sources Part A Recovery Utilization and Environmental Effects (2020) Vol. 42, Iss. 22, pp. 2715-2730
Closed Access | Times Cited: 33

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