Cited by Machine learning-based inertia estimation in power systems: a review of methods and challenges

Forecasting Corporate Financial Performance Using Deep Learning with Environmental, Social, and Governance Data DOI

Wei‐Hsiu Hsu, Ying-Lei Lin, Jung-Pin Lai

et al.

Electronics, Journal Year: 2025, Volume and Issue: 14(3), P. 417 - 417

Published: Jan. 21, 2025

In recent years, extensive research has focused on the relationship between corporate social responsibility (CSR) and financial performance. While past studies have explored this connection, they often faced challenges in quantitatively assessing effectiveness of CSR initiatives. However, advancements methodologies development Environmental, Social, Governance (ESG) measurement dimensions led to creation more robust evaluation criteria. These criteria use ESG scores as primary reference indicators for activities. This study aims utilize from InfoHub website Taiwan Stock Exchange Corporation (TSEC) benchmarks, comprising 15 items environmental (E), (S), governance (G) form predict The data cover years 2021–2022 listed companies, using return assets (ROA) equity (ROE) measures With rapid artificial intelligence applications machine learning deep (DL) proliferated across many fields. analyze remains rare. Therefore, employs models performance based performance, utilizing both classification regression approaches. Numerical results indicate that two models, Long Short-Term Memory (LSTM) Convolutional Neural Network (CNN), outperform other tasks, respectively. Consequently, techniques prove be feasible, effective, efficient alternatives predicting corporations’ metrics.

Language: Английский

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Reconstruction of Missing Data Completely at Random for Trains Based on Improved GAN DOI

Jing He, Xin Chen, Changfan Zhang

et al.

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 117 - 132

Published: Jan. 1, 2025

Language: Английский

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Extracting Narrative Events in Andersen’s Fairy Tales Using a Hybrid BERT-LSTM Model DOI

Aji Prasetya Wibawa, Aji Prasetya Wibawa,

Wahyu Sakti Gunawan Irianto

et al.

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 355 - 372

Published: Jan. 1, 2025

Language: Английский

Citations

Machine learning-based inertia estimation in power systems: a review of methods and challenges DOI

Santosh Diggikar,

Arunkumar Patil,

Siddhant Satyapal Katkar

et al.

Energy Informatics, Journal Year: 2025, Volume and Issue: 8(1)

Published: April 30, 2025

Language: Английский

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