{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:52:37Z","timestamp":1777704757408,"version":"3.51.4"},"reference-count":0,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[1996,11,1]],"date-time":"1996-11-01T00:00:00Z","timestamp":846806400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[1996,11]]},"abstract":"<jats:p>A tool that can be used to assess structural safety is fault tree analysis (FTA) , which depends primarily on quantitative information. However, in many cases, safety assessment of civil engineering structures is based on subjective judgement. To improve the traditional FTA, the authors use the fuzzy set concept and introduce fuzzy fault tree analysis (FFTA). The development and potential application of FFTA operators (gates) are elaborated. Several example and an illustration are presented to justify the usefulness of FFTA.<\/jats:p>","DOI":"10.3233\/ifs-1996-4403","type":"journal-article","created":{"date-parts":[[2019,12,2]],"date-time":"2019-12-02T17:38:48Z","timestamp":1575308328000},"page":"269-280","source":"Crossref","is-referenced-by-count":2,"title":["Fuzzy Fault Tree Analysis for Structural Safety"],"prefix":"10.1177","volume":"4","author":[{"given":"Tomoyuki","family":"Fujino","sequence":"first","affiliation":[{"name":"Japan Highway Public Corporation, 1-18-1 Toranomon, Minato-ku, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fabian C.","family":"Hadipriono","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, The Ohio State University, 2070 Neil Avenue, Columbus, OH 43210"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[1996,11]]},"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-1996-4403","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-1996-4403","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:41:56Z","timestamp":1777455716000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/IFS-1996-4403"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1996,11]]},"references-count":0,"journal-issue":{"issue":"4","published-print":{"date-parts":[[1996,11]]}},"alternative-id":["10.3233\/IFS-1996-4403"],"URL":"https:\/\/doi.org\/10.3233\/ifs-1996-4403","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[1996,11]]}}}