A novel method for long-term power demand prediction using enhanced data decomposition and neural network with integrated uncertainty analysis: A Cuba case study DOI
Manuel Soto Calvo, Han Soo Lee, Sylvester William Chisale

и другие.

Applied Energy, Год журнала: 2024, Номер 372, С. 123864 - 123864

Опубликована: Июль 9, 2024

Язык: Английский

Enhancing accuracy in point-interval load forecasting: A new strategy based on data augmentation, customized deep learning, and weighted linear error correction DOI
Weican Liu, Zhirui Tian, Yuyan Qiu

и другие.

Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 126686 - 126686

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

4

Enhanced load forecasting for distributed multi-energy system: A stacking ensemble learning method with deep reinforcement learning and model fusion DOI

Xiaoxiao Ren,

Xin Tian, Kai Wang

и другие.

Energy, Год журнала: 2025, Номер unknown, С. 135031 - 135031

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

4

AI-Driven Innovations in Building Energy Management Systems: A Review of Potential Applications and Energy Savings DOI Creative Commons

Dalia Mohammed Talat Ebrahim Ali,

Violeta Motuzienė, Rasa Džiugaitė-Tumėnienė

и другие.

Energies, Год журнала: 2024, Номер 17(17), С. 4277 - 4277

Опубликована: Авг. 27, 2024

Despite the tightening of energy performance standards for buildings in various countries and increased use efficient renewable technologies, it is clear that sector needs to change more rapidly meet Net Zero Emissions (NZE) scenario by 2050. One problems have been analyzed intensively recent years operation much than they were designed to. This problem, known as gap, found many often attributed poor management building systems. The application Artificial Intelligence (AI) Building Energy Management Systems (BEMS) has untapped potential address this problem lead sustainable buildings. paper reviews different AI-based models proposed applications with intention reduce consumption. It compares evaluated reviewed papers presenting accuracy error rates model identifies where greatest savings could be achieved, what extent. review showed offices (up 37%) when employ AI HVAC control optimization. In residential educational buildings, lower intelligence existing BEMS results smaller 23% 21%, respectively).

Язык: Английский

Процитировано

15

A deep learning integrated framework for predicting stock index price and fluctuation via singular spectrum analysis and particle swarm optimization DOI
Chia‐Hung Wang, Jinchen Yuan,

Yingping Zeng

и другие.

Applied Intelligence, Год журнала: 2024, Номер 54(2), С. 1770 - 1797

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

13

An attention-based multi-input LSTM with sliding window-based two-stage decomposition for wind speed forecasting DOI
Dongchuan Yang, Mingzhu Li, Ju’e Guo

и другие.

Applied Energy, Год журнала: 2024, Номер 375, С. 124057 - 124057

Опубликована: Авг. 9, 2024

Язык: Английский

Процитировано

13

Multi-energy load forecasting via hierarchical multi-task learning and spatiotemporal attention DOI
Cairong Song,

Haidong Yang,

Jianyang Cai

и другие.

Applied Energy, Год журнала: 2024, Номер 373, С. 123788 - 123788

Опубликована: Июль 14, 2024

Язык: Английский

Процитировано

10

Integrated energy short-term multivariate load forecasting based on PatchTST secondary decoupling reconstruction for progressive layered extraction multi-task learning network DOI
Zhijian Qu,

Yan Meng,

Xinxing Hou

и другие.

Expert Systems with Applications, Год журнала: 2025, Номер 269, С. 126446 - 126446

Опубликована: Янв. 7, 2025

Язык: Английский

Процитировано

1

Application of artificial neural networks in predicting the performance of ice thermal energy storage systems DOI Creative Commons

O.Y. Odufuwa,

Lagouge K. Tartibu, K. Kusakana

и другие.

Journal of Energy Storage, Год журнала: 2024, Номер 95, С. 112547 - 112547

Опубликована: Июнь 14, 2024

Язык: Английский

Процитировано

6

A federated and transfer learning based approach for households load forecasting DOI
Gurjot Singh, Jatin Bedi

Knowledge-Based Systems, Год журнала: 2024, Номер 299, С. 111967 - 111967

Опубликована: Май 24, 2024

Язык: Английский

Процитировано

4

Analysis of aggregated load consumption forecasting in short, medium and long term horizons using Dynamic Mode Decomposition DOI Creative Commons
Marc Carrillo Muñoz, Mònica Aragüés‐Peñalba, Antonio E. Saldaña-González

и другие.

Energy Reports, Год журнала: 2024, Номер 12, С. 1000 - 1013

Опубликована: Июль 10, 2024

Язык: Английский

Процитировано

4