Research on parameter optimisation of dynamic priority scheduling algorithm based on improved reinforcement learning-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Research on parameter optimisation of dynamic priority scheduling algorithm based on improved reinforcement learning

Published:2020-06-15 Issue:16 Volume:14 Page:3171-3178
ISSN:1751-8695
Container-title:IET Generation, Transmission & Distribution
language:en
Short-container-title:IET Generation, Transmission & Distribution

Author:

Meng Shanshan¹,Zhu Qiang²,Xia Fei¹,Lu Jianfeng³

Affiliation:

1. College of Automation EngineeringShanghai University of Electric PowerShanghai200090People's Republic of China

2. Shanghai Automation Instrument Co., Ltd.Shanghai200230People's Republic of China

3. College of Electronics and Information EngineeringTongji UniversityShanghai201804People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-gtd.2019.1468

Reference38 articles.

1. Tao L. Rongfa Q. Zhenjiang G. et al.: ‘Research on power system active power scheduling strategy adapted to large‐scale wind power grid‐connected’.2018 3rd Int. Conf. on Smart City and Systems Engineering (ICSCSE) Xiamen People's Republic of China 2018 pp.482–486

2. Bakirtzis E.A. Ntomaris A.V. Kardakos E.G. et al.: ‘Bakirtzis. A unified unit commitment–economic dispatch model for short‐term power system scheduling under high wind energy penetration’.11th Int. Conf. on the European Energy Market (EEM14) Krakow Poland 2014 pp.1–6

3. Liu D.‐n. Jiang X.‐f. Hu B.‐q. et al.: ‘Real‐time scheduling feedback fuzzy control system based on area control error and power generation error’.2012 9th International Conference on Fuzzy Systems and Knowledge Discovery Sichuan People's Republic of China 2012 pp.352–355

4. Nghiem T. Behl M. Pappas G.J. et al.: ‘Scheduling of control systems for peak power reduction’.2011 Int. Green Computing Conf. and Workshops Orlando FL USA 2011 pp.1–8

5. Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment

Cited by 6 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. An improved genetic algorithm based on reinforcement learning for aircraft assembly scheduling problem;Computers & Industrial Engineering;2024-07

2. Key technologies of end-side computing power network based on multi-granularity and multi-level end-side computing power scheduling;Journal of Computational Methods in Sciences and Engineering;2024-05-10

3. Scheduling Model for Prefabricated Component Assembly, Production, and Transportation Stage Based on GA for Prefabricated Buildings;IEEE Access;2024

4. A Data Centre Traffic Scheduling Algorithm Based on Task Type;Lecture Notes in Electrical Engineering;2023

5. An adaptive heuristic algorithm based on reinforcement learning for ship scheduling optimization problem;Ocean & Coastal Management;2022-11

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3