Deep-Chain Echo State Network With Explainable Temporal Dependence for Complex Building Energy Prediction

Author:

Jiang Ruiqi1ORCID,Zeng Shaoxiong1ORCID,Song Qing2,Wu Zhou1ORCID

Affiliation:

1. School of Automation, Chongqing University, Chongqing, China

2. Pattern Recognition and Intelligent Vision Laboratory, Beijing University of Posts and Telecommunications, Beijing, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Science and Technology Research Project of Chongqing Education Commission

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Affinity-Driven Transfer Learning for Load Forecasting;Sensors;2024-09-06

2. NOx Concentration Prediction With a Flexible Cascaded Echo-State Network in a Cement Clinker Calcination System;IEEE Transactions on Industrial Informatics;2024-07

3. Multi-scale deep echo state network for time series prediction;Neural Computing and Applications;2024-04-25

4. Leveraging Artificial Intelligence to Bolster the Energy Sector in Smart Cities: A Literature Review;Energies;2024-01-10

5. Explainable and Interpretable Artificial Intelligence as a Service for Green Smart Cities and Communities;2023 IEEE 15th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM);2023-11-19

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