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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:

Very Short-Term Solar Generation Forecasting Based on LSTM with Temporal Attention Mechanism
Cheng Pan, Jie Tan, Dandan Feng, et al.
(2019), pp. 267-271
Closed Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

Machine learning in photovoltaic systems: A review
Jorge Felipe Gaviria, Gabriel Narváez, Camilo Andrés Guillén, et al.
Renewable Energy (2022) Vol. 196, pp. 298-318
Open Access | Times Cited: 88
NOA-LSTM: An efficient LSTM cell architecture for time series forecasting
Hemant Yadav, Amit Thakkar
Expert Systems with Applications (2023) Vol. 238, pp. 122333-122333
Closed Access | Times Cited: 49
An Experimental Review on Deep Learning Architectures for Time Series Forecasting
Pedro Lara-Benítez, Manuel Carranza-García, José C. Riquelme
International Journal of Neural Systems (2020) Vol. 31, Iss. 03, pp. 2130001-2130001
Open Access | Times Cited: 99
A hybrid model for multi-step coal price forecasting using decomposition technique and deep learning algorithms
Kefei Zhang, Hua Cao, Jesse Van Griensven Thé, et al.
Applied Energy (2021) Vol. 306, pp. 118011-118011
Closed Access | Times Cited: 83
A Review on Deep Sequential Models for Forecasting Time Series Data
Dozdar Mahdi Ahmed, Masoud Muhammed Hassan, Ramadhan J. Mstafa
Applied Computational Intelligence and Soft Computing (2022) Vol. 2022, pp. 1-19
Open Access | Times Cited: 49
Deep Learning for Time Series Forecasting: Advances and Open Problems
Angelo Casolaro, Vincenzo Capone, Gennaro Iannuzzo, et al.
Information (2023) Vol. 14, Iss. 11, pp. 598-598
Open Access | Times Cited: 38
Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review
Mohamed Massaoudi, Inès Chihi, Haitham Abu‐Rub, et al.
IEEE Access (2021) Vol. 9, pp. 136593-136615
Open Access | Times Cited: 50
Prediction-based peer-to-peer energy transaction market design for smart grids
I. Chien, P. Karthikeyan, Pao‐Ann Hsiung
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107190-107190
Closed Access | Times Cited: 14
Short-Term Load Forecasting Based on CNN-BiLSTM with Bayesian Optimization and Attention Mechanism
Kai Miao, Qiang Hua, Hui-Feng Shi
Lecture notes in computer science (2021), pp. 116-128
Closed Access | Times Cited: 25
Determination of the Concepts of Building a Solar Power Forecasting Model
Alla Bosak, Dmytro Matushkin, Volodymyr Dubovyk, et al.
Scientific Horizons (2022) Vol. 24, Iss. 10, pp. 9-16
Open Access | Times Cited: 18
Evaluating different artificial neural network forecasting approaches for optimizing district heating network operation
Lilli Frison, Simon Gölzhäuser, Moritz Bitterling, et al.
Energy (2024) Vol. 307, pp. 132745-132745
Open Access | Times Cited: 3
Short-term photovoltaic power forecasting using parameter-optimized variational mode decomposition and attention-based neural network
Kejun Tao, Jinghao Zhao, Nana Wang, et al.
Energy Sources Part A Recovery Utilization and Environmental Effects (2024) Vol. 46, Iss. 1, pp. 3807-3824
Closed Access | Times Cited: 2
Short‐term load forecasting based on CNN‐BiLSTM with Bayesian optimization and attention mechanism
Hui-Feng Shi, Kai Miao, Xiaochen Ren
Concurrency and Computation Practice and Experience (2021) Vol. 35, Iss. 17
Closed Access | Times Cited: 17
Univariate and Multivariate LSTM Models for One Step and Multistep PV Power Forecasting
Tariq Limouni, Reda Yaagoubi, K. Bouziane, et al.
International Journal of Renewable Energy Development (2022) Vol. 11, Iss. 3, pp. 815-828
Open Access | Times Cited: 9
Intelligent Load Control with Embedded Automation and Mobile Application
Kalyan Dusarlapudi, Appana Naga Suresh, Basa Naveen, et al.
(2024), pp. 1-7
Closed Access | Times Cited: 1
A novel bifold-attention-LSTM for analyzing PM2.5 concentration-based multi-station data time series
Andri Pranolo, Xiaofeng Zhou, Yingchi Mao
International Journal of Data Science and Analytics (2024)
Closed Access | Times Cited: 1
Dual-Path Information Fusion and Twin Attention-Driven Global Modeling for Solar Irradiance Prediction
Yushi Yang, Zhanjun Tang, Zhiyuan Li, et al.
Sensors (2023) Vol. 23, Iss. 17, pp. 7469-7469
Open Access | Times Cited: 4
Meta-learning for few-shot time series forecasting
Feng Xiao, Lu Liu, Jiayu Han, et al.
Journal of Intelligent & Fuzzy Systems (2022) Vol. 43, Iss. 1, pp. 325-341
Closed Access | Times Cited: 6
Improving classification‐based nowcasting of radiation fog with machine learning based on filtered and preprocessed temporal data
Adrian Schütz, Adrian Schütz, Jörg Bendix, et al.
Quarterly Journal of the Royal Meteorological Society (2023) Vol. 150, Iss. 759, pp. 577-596
Open Access | Times Cited: 2
Short-time traffic flow forecast with weather characteristics
Mingzhou Wang, Tian Shan, Chao Chen, et al.
(2020), pp. 142-145
Closed Access | Times Cited: 5
Research on Pricing and Replenishment Strategies of Supermarkets Based on PSO-LSTM- Transformer Models
Jiacheng Song, Jing Huang, Yukai Gao, et al.
Journal of Education Humanities and Social Sciences (2024) Vol. 25, pp. 176-182
Open Access
TVGCN: Time-varying graph convolutional networks for multivariate and multifeature spatiotemporal series prediction
Feiyan Sun, Wenning Hao, Ao Zou, et al.
Science Progress (2024) Vol. 107, Iss. 3
Open Access
Ultra-short-term solar PV power forecasting based on cloud displacement vector using multi-channel satellite and NWP data
Rui Gao, Xuemin Zhang, Zhao Zhen, et al.
(2021), pp. 5800-5805
Closed Access | Times Cited: 4
A Review On Breaking the Limits of Time Series Forecasting Algorithms
Ammar Raneez, Torin Wirasingha
2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC) (2023), pp. 0482-0488
Closed Access | Times Cited: 1
ANALYSIS OF FACTORS FOR FORECASTING ELECTRIC POWER GENERATION BY SOLAR POWER PLANTS
Dmytro Matushkin, Alla Bosak, Leonid Kulakovskyi
POWER ENGINEERING economics technique ecology (2020), Iss. 4
Open Access | Times Cited: 3
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