{"title":"异常环境安全评价的模糊代数不确定性分析","authors":"J. A. Cooper","doi":"10.1109/ICNN.1994.374551","DOIUrl":null,"url":null,"abstract":"Many safety (risk) analyses depend on uncertain inputs and on mathematical models chosen from various alternatives, but give fixed results (implying no uncertainty). Conventional uncertainty analyses help, but are also based on assumptions and models, the accuracy of which may be difficult to assure. Some of the models and assumptions that on cursory examination seem reasonable can be misleading. As a result, quantitative assessments, even those accompanied by uncertainty measures, can give unwarranted impressions of accuracy. Since analysis results can be a major contributor to a safety-measure decision process, risk management depends on relating uncertainty to only the information available. The uncertainties due to abnormal environments are even more challenging than those in normal-environment safety assessments; and therefore require an even more cautious approach. A fuzzy algebra analysis is proposed in this paper that has the potential to appropriately reflect the information available and portray uncertainties well, especially for abnormal environments.<<ETX>>","PeriodicalId":209128,"journal":{"name":"Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Fuzzy-algebra uncertainty analysis for abnormal-environment safety assessment\",\"authors\":\"J. A. Cooper\",\"doi\":\"10.1109/ICNN.1994.374551\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many safety (risk) analyses depend on uncertain inputs and on mathematical models chosen from various alternatives, but give fixed results (implying no uncertainty). Conventional uncertainty analyses help, but are also based on assumptions and models, the accuracy of which may be difficult to assure. Some of the models and assumptions that on cursory examination seem reasonable can be misleading. As a result, quantitative assessments, even those accompanied by uncertainty measures, can give unwarranted impressions of accuracy. Since analysis results can be a major contributor to a safety-measure decision process, risk management depends on relating uncertainty to only the information available. The uncertainties due to abnormal environments are even more challenging than those in normal-environment safety assessments; and therefore require an even more cautious approach. A fuzzy algebra analysis is proposed in this paper that has the potential to appropriately reflect the information available and portray uncertainties well, especially for abnormal environments.<<ETX>>\",\"PeriodicalId\":209128,\"journal\":{\"name\":\"Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNN.1994.374551\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNN.1994.374551","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fuzzy-algebra uncertainty analysis for abnormal-environment safety assessment
Many safety (risk) analyses depend on uncertain inputs and on mathematical models chosen from various alternatives, but give fixed results (implying no uncertainty). Conventional uncertainty analyses help, but are also based on assumptions and models, the accuracy of which may be difficult to assure. Some of the models and assumptions that on cursory examination seem reasonable can be misleading. As a result, quantitative assessments, even those accompanied by uncertainty measures, can give unwarranted impressions of accuracy. Since analysis results can be a major contributor to a safety-measure decision process, risk management depends on relating uncertainty to only the information available. The uncertainties due to abnormal environments are even more challenging than those in normal-environment safety assessments; and therefore require an even more cautious approach. A fuzzy algebra analysis is proposed in this paper that has the potential to appropriately reflect the information available and portray uncertainties well, especially for abnormal environments.<>