一种基于人工神经网络的连续数年维修调度方案

[1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems Pub Date : 1993-04-19 DOI:10.1109/ANN.1993.264326

H. Sasaki, H. Choshi, Y. Takiuchi, J. Kubokawa

{"title":"一种基于人工神经网络的连续数年维修调度方案","authors":"H. Sasaki, H. Choshi, Y. Takiuchi, J. Kubokawa","doi":"10.1109/ANN.1993.264326","DOIUrl":null,"url":null,"abstract":"This paper describes a method of solving the maintenance scheduling problem of thermal power station units by making use of artificial neural networks, which can handle inequality constraints effectively. In the problem formulation, different classes of maintenance works and several consecutive years are considered to obtain a more realistic solution. The problem has been mapped on artificial neural networks and solved by a network simulator.<<ETX>>","PeriodicalId":121897,"journal":{"name":"[1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems","volume":"113 4 Suppl 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"A solution of maintenance scheduling covering several consecutive years by artificial neural networks\",\"authors\":\"H. Sasaki, H. Choshi, Y. Takiuchi, J. Kubokawa\",\"doi\":\"10.1109/ANN.1993.264326\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a method of solving the maintenance scheduling problem of thermal power station units by making use of artificial neural networks, which can handle inequality constraints effectively. In the problem formulation, different classes of maintenance works and several consecutive years are considered to obtain a more realistic solution. The problem has been mapped on artificial neural networks and solved by a network simulator.<<ETX>>\",\"PeriodicalId\":121897,\"journal\":{\"name\":\"[1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems\",\"volume\":\"113 4 Suppl 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ANN.1993.264326\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANN.1993.264326","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 15

摘要

本文介绍了一种利用人工神经网络解决火电厂机组维修调度问题的方法，该方法能有效地处理不等式约束。在问题的表述中，考虑了不同类别的维修工程和连续数年，以获得更现实的解决方案。该问题已映射到人工神经网络上，并通过网络模拟器解决。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

A solution of maintenance scheduling covering several consecutive years by artificial neural networks

This paper describes a method of solving the maintenance scheduling problem of thermal power station units by making use of artificial neural networks, which can handle inequality constraints effectively. In the problem formulation, different classes of maintenance works and several consecutive years are considered to obtain a more realistic solution. The problem has been mapped on artificial neural networks and solved by a network simulator.<>

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

[1993] Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems

自引率

0.00%

发文量