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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:

Day-ahead power forecasting in a large-scale photovoltaic plant based on weather classification using LSTM
Mingming Gao, Jianjing Li, Feng Hong, et al.
Energy (2019) Vol. 187, pp. 115838-115838
Closed Access | Times Cited: 238

Showing 1-25 of 238 citing articles:

Deep Learning for Time Series Forecasting: A Survey
J. F. Torres, Dalil Hadjout, Abderrazak Sebaa, et al.
Big Data (2020) Vol. 9, Iss. 1, pp. 3-21
Closed Access | Times Cited: 509
Taxonomy research of artificial intelligence for deterministic solar power forecasting
Huaizhi Wang, Yangyang Liu, Bin Zhou, et al.
Energy Conversion and Management (2020) Vol. 214, pp. 112909-112909
Closed Access | Times Cited: 266
Advanced Methods for Photovoltaic Output Power Forecasting: A Review
A. Mellit, Alessandro Pavan, Emanuèle Ogliari, et al.
Applied Sciences (2020) Vol. 10, Iss. 2, pp. 487-487
Open Access | Times Cited: 249
Deep learning neural networks for short-term photovoltaic power forecasting
A. Mellit, Alessandro Pavan, Vanni Lughi
Renewable Energy (2021) Vol. 172, pp. 276-288
Closed Access | Times Cited: 237
A review and taxonomy of wind and solar energy forecasting methods based on deep learning
Ghadah Alkhayat, Rashid Mehmood
Energy and AI (2021) Vol. 4, pp. 100060-100060
Open Access | Times Cited: 204
Day-ahead hourly photovoltaic power forecasting using attention-based CNN-LSTM neural network embedded with multiple relevant and target variables prediction pattern
Jiaqi Qu, Zheng Qian, Yan Pei
Energy (2021) Vol. 232, pp. 120996-120996
Closed Access | Times Cited: 201
Deep Learning Based Surface Irradiance Mapping Model for Solar PV Power Forecasting Using Sky Image
Zhao Zhen, Jiaming Liu, Zhanyao Zhang, et al.
IEEE Transactions on Industry Applications (2020), pp. 1-1
Closed Access | Times Cited: 184
Photovoltaic power forecasting based on GA improved Bi-LSTM in microgrid without meteorological information
Zhen Hao, Dongxiao Niu, Keke Wang, et al.
Energy (2021) Vol. 231, pp. 120908-120908
Closed Access | Times Cited: 145
Time series forecasting for hourly photovoltaic power using conditional generative adversarial network and Bi-LSTM
Xiaoqiao Huang, Qiong Li, Yonghang Tai, et al.
Energy (2022) Vol. 246, pp. 123403-123403
Closed Access | Times Cited: 139
A Simplified LSTM Neural Networks for One Day-Ahead Solar Power Forecasting
Chun‐Hung Liu, Jyh‐Cherng Gu, Ming‐Ta Yang
IEEE Access (2021) Vol. 9, pp. 17174-17195
Open Access | Times Cited: 132
A novel hybrid model based on nonlinear weighted combination for short-term wind power forecasting
Jiandong Duan, Peng Wang, Wentao Ma, et al.
International Journal of Electrical Power & Energy Systems (2021) Vol. 134, pp. 107452-107452
Closed Access | Times Cited: 111
A novel long term solar photovoltaic power forecasting approach using LSTM with Nadam optimizer: A case study of India
Jatin Sharma, Sameer Soni, Priyanka Paliwal, et al.
Energy Science & Engineering (2022) Vol. 10, Iss. 8, pp. 2909-2929
Open Access | Times Cited: 77
Machine Learning Based Solar Photovoltaic Power Forecasting: A Review and Comparison
Jwaone Gaboitaolelwe, Adamu Murtala Zungeru, Abid Yahya, et al.
IEEE Access (2023) Vol. 11, pp. 40820-40845
Open Access | Times Cited: 77
Improved multistep ahead photovoltaic power prediction model based on LSTM and self-attention with weather forecast data
Zehuan Hu, Yuan Gao, Siyu JI, et al.
Applied Energy (2024) Vol. 359, pp. 122709-122709
Closed Access | Times Cited: 67
Multi-scale solar radiation and photovoltaic power forecasting with machine learning algorithms in urban environment: A state-of-the-art review
Jia Tian, Ryozo Ooka, Doyun Lee
Journal of Cleaner Production (2023) Vol. 426, pp. 139040-139040
Closed Access | Times Cited: 46
A Comprehensive Review on Ensemble Solar Power Forecasting Algorithms
Negar Rahimi, Sejun Park, Wonseok Choi, et al.
Journal of Electrical Engineering and Technology (2023) Vol. 18, Iss. 2, pp. 719-733
Open Access | Times Cited: 44
Photovoltaic systems operation and maintenance: A review and future directions
Hind Abdulla, Andrei Sleptchenko, Ammar Nayfeh
Renewable and Sustainable Energy Reviews (2024) Vol. 195, pp. 114342-114342
Open Access | Times Cited: 28
A satellite image data based ultra-short-term solar PV power forecasting method considering cloud information from neighboring plant
Fei Wang, Xiaoxing Lu, Shengwei Mei, et al.
Energy (2021) Vol. 238, pp. 121946-121946
Closed Access | Times Cited: 100
Solar Photovoltaic Forecasting of Power Output Using LSTM Networks
Maria Konstantinou, Stefani Peratikou, Alexandros G. Charalambides
Atmosphere (2021) Vol. 12, Iss. 1, pp. 124-124
Open Access | Times Cited: 95
Operational day-ahead solar power forecasting for aggregated PV systems with a varying spatial distribution
Lennard Visser, Tarek AlSkaif, Wilfried van Sark
Renewable Energy (2021) Vol. 183, pp. 267-282
Open Access | Times Cited: 91
Adaptive optimal fuzzy logic based energy management in multi-energy microgrid considering operational uncertainties
Wei Dong, Qiang Yang, Xinli Fang, et al.
Applied Soft Computing (2020) Vol. 98, pp. 106882-106882
Closed Access | Times Cited: 84
Big data driven predictive production planning for energy-intensive manufacturing industries
Shuaiyin Ma, Yingfeng Zhang, Jingxiang Lv, et al.
Energy (2020) Vol. 211, pp. 118320-118320
Closed Access | Times Cited: 79
Hour-ahead photovoltaic generation forecasting method based on machine learning and multi objective optimization algorithm
Jianzhou Wang, Yilin Zhou, Zhiwu Li
Applied Energy (2022) Vol. 312, pp. 118725-118725
Closed Access | Times Cited: 65
Review on Photovoltaic Power and Solar Resource Forecasting: Current Status and Trends
Tatiane Carolyne Carneiro, Paulo César Marques de Carvalho, Heron Alves dos Santos, et al.
Journal of Solar Energy Engineering (2021) Vol. 144, Iss. 1
Closed Access | Times Cited: 58
A point prediction method based automatic machine learning for day-ahead power output of multi-region photovoltaic plants
Wei Zhao, Haoran Zhang, Jianqin Zheng, et al.
Energy (2021) Vol. 223, pp. 120026-120026
Closed Access | Times Cited: 56
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