H. Gabbar, Sk Sami Al Jabar, Hassan A. Hassan, Jing Ren
{"title":"智能经验保留系统:核电站运行维护的挑战与局限","authors":"H. Gabbar, Sk Sami Al Jabar, Hassan A. Hassan, Jing Ren","doi":"10.1109/MSMC.2021.3098981","DOIUrl":null,"url":null,"abstract":"This article presents an intelligent experience retention system (IERS), which is designed to overcome challenges and limitations of capturing human experience related to operating procedures for plant operation and maintenance in nuclear power plants. It is time-consuming to find specific information from thousands of input documents. Less experienced employees cannot operate complex tasks due to having less knowledge and training about the documents and their operation. Research gaps in current knowledge structuring and retrieval methods are discussed and used to identify essential features to achieve effective methods to manage instructive text (iText) related to learning and answering queries connected to operating procedures. Knowledge structure is proposed to represent inputs from documents, data, text, and voice related to operation and maintenance instructions in nuclear power plants. Human experience is captured and integrated within the structured knowledge in an integrated scheme, called the human experience semantic network (HESN), which includes deterministic, qualitative, and probabilistic parameters and attributes that are captured and dynamically tuned throughout the execution of the system.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"12 1","pages":"31-34"},"PeriodicalIF":1.9000,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Intelligent Experience Retention System: Challenges and Limitations for Operation and Maintenance in Nuclear Power Plants\",\"authors\":\"H. Gabbar, Sk Sami Al Jabar, Hassan A. Hassan, Jing Ren\",\"doi\":\"10.1109/MSMC.2021.3098981\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents an intelligent experience retention system (IERS), which is designed to overcome challenges and limitations of capturing human experience related to operating procedures for plant operation and maintenance in nuclear power plants. It is time-consuming to find specific information from thousands of input documents. Less experienced employees cannot operate complex tasks due to having less knowledge and training about the documents and their operation. Research gaps in current knowledge structuring and retrieval methods are discussed and used to identify essential features to achieve effective methods to manage instructive text (iText) related to learning and answering queries connected to operating procedures. Knowledge structure is proposed to represent inputs from documents, data, text, and voice related to operation and maintenance instructions in nuclear power plants. Human experience is captured and integrated within the structured knowledge in an integrated scheme, called the human experience semantic network (HESN), which includes deterministic, qualitative, and probabilistic parameters and attributes that are captured and dynamically tuned throughout the execution of the system.\",\"PeriodicalId\":43649,\"journal\":{\"name\":\"IEEE Systems Man and Cybernetics Magazine\",\"volume\":\"12 1\",\"pages\":\"31-34\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2021-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Systems Man and Cybernetics Magazine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MSMC.2021.3098981\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, CYBERNETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Systems Man and Cybernetics Magazine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MSMC.2021.3098981","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
An Intelligent Experience Retention System: Challenges and Limitations for Operation and Maintenance in Nuclear Power Plants
This article presents an intelligent experience retention system (IERS), which is designed to overcome challenges and limitations of capturing human experience related to operating procedures for plant operation and maintenance in nuclear power plants. It is time-consuming to find specific information from thousands of input documents. Less experienced employees cannot operate complex tasks due to having less knowledge and training about the documents and their operation. Research gaps in current knowledge structuring and retrieval methods are discussed and used to identify essential features to achieve effective methods to manage instructive text (iText) related to learning and answering queries connected to operating procedures. Knowledge structure is proposed to represent inputs from documents, data, text, and voice related to operation and maintenance instructions in nuclear power plants. Human experience is captured and integrated within the structured knowledge in an integrated scheme, called the human experience semantic network (HESN), which includes deterministic, qualitative, and probabilistic parameters and attributes that are captured and dynamically tuned throughout the execution of the system.