Explainable, Deep Reinforcement Learning–Based Decision Making for Operations and Maintenance

IF 1.5 4区工程技术 Q2 NUCLEAR SCIENCE & TECHNOLOGY

Nuclear Technology Pub Date : 2024-08-02 DOI:10.1080/00295450.2024.2377034

Ryan M. Spangler, Mahsa Raeisinezhad, Daniel G. Cole

引用次数: 0

Abstract

This paper presents research that integrates condition monitoring and prognostics with decision making for nuclear power plant operations and maintenance aimed at reducing lifetime maintenance and ...

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可解释的、基于深度强化学习的运维决策制定

本文介绍了将状态监测和预报与核电厂运营和维护决策相结合的研究，旨在减少寿命期内的维护和...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nuclear Technology 工程技术-核科学技术

CiteScore

3.40

自引率

6.70%

发文量

116

审稿时长

4-8 weeks

期刊介绍： Nuclear Technology aims to be the leading international publication reporting new information in the practical applications of nuclear science and technology. We publish technical papers, technical notes, critical reviews, rapid communications, book reviews, and letters to the editor on all phases of applications of fundamental research to nuclear technology.