{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,2]],"date-time":"2022-04-02T02:18:00Z","timestamp":1648865880094},"reference-count":2,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Artif. Intell. Tools"],"published-print":{"date-parts":[[2004,9]]},"abstract":"<jats:p> The huge and complicated plants such as nuclear power stations are likely to cause the operators to make mistakes due to a variety of inexplicable reasons and symptoms in case of emergency. That's why the prevention system assisting the operators is being developed for. First of all, I suggest an improved fuzzy diagnosis. Secondly, I want to demonstrate that a classification system of nuclear plant's accident investigating the causes of accidents foresees possible problems, and maintains the reliability of the diagnostic reports in spite of improper working in part. <\/jats:p><jats:p> In the event of emergency in a nuclear plant, a lot of operational steps enable the operators to find out what caused the problems based on an emergent operating plan. Our system is able to classify their types within twenty to thirty seconds. As so, we expect the system to put down the accidents right after the rapid detection of the damage control-method concerned. <\/jats:p>","DOI":"10.1142\/s0218213004001740","type":"journal-article","created":{"date-parts":[[2004,11,1]],"date-time":"2004-11-01T06:51:20Z","timestamp":1099291880000},"page":"691-703","source":"Crossref","is-referenced-by-count":1,"title":["MULTIMEDIA EXPERT SYSTEM FOR A NUCLEAR POWER PLANT ACCIDENT DIAGNOSIS USING A FUZZY INFERENCE METHOD"],"prefix":"10.1142","volume":"13","author":[{"given":"MAL-REY","family":"LEE","sequence":"first","affiliation":[{"name":"School of Electronics &amp; Information Engineering,  ChonBuk National University, 664-14, DeokJin-Dong, JeonJu, ChonBuk, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"HEAI-JO","family":"KANG","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering,  Mokwon University, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"TAE EUN","family":"KIM","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering,  NamSeoul University, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1016\/S0020-7373(76)80027-2"},{"key":"rf2","first-page":"38","volume":"30","author":"Pappies C. P.","journal-title":"Information and Control"}],"container-title":["International Journal on Artificial Intelligence Tools"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218213004001740","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T22:30:33Z","timestamp":1565130633000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218213004001740"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2004,9]]},"references-count":2,"journal-issue":{"issue":"03","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[2004,9]]}},"alternative-id":["10.1142\/S0218213004001740"],"URL":"https:\/\/doi.org\/10.1142\/s0218213004001740","relation":{},"ISSN":["0218-2130","1793-6349"],"issn-type":[{"value":"0218-2130","type":"print"},{"value":"1793-6349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2004,9]]}}}