Dynamic Feature Selection for Solar Irradiance Forecasting Based on Deep Reinforcement Learning-Reference-Cited by-同舟云学术

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Dynamic Feature Selection for Solar Irradiance Forecasting Based on Deep Reinforcement Learning

Published:2023-01 Issue:1 Volume:59 Page:533-543
ISSN:0093-9994
Container-title:IEEE Transactions on Industry Applications
language:
Short-container-title:IEEE Trans. on Ind. Applicat.

Author:

Lyu Cheng¹,Eftekharnejad Sara¹^ORCID,Basumallik Sagnik²^ORCID,Xu Chongfang³

Affiliation:

1. Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USA

2. Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV, USA

3. Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA

Funder

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Control and Systems Engineering

Link

https://ieeexplore.ieee.org/ielam/28/10021929/9893318-aam.pdf

Reference50 articles.

1. Human-level control through deep reinforcement learning;mnih;Natural,2015

3. Spectral Clustering

4. Spectral embedded generalized mean based k-nearest neighbors clustering with S-distance

5. A novel and efficient data point neighborhood construction algorithm based on Apollonius circle

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