A decision-support system to improve damage survivability of submarine
DC Field | Value | Language |
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dc.contributor.author | Lee, D | - |
dc.contributor.author | Lee, J | - |
dc.contributor.author | Lee, KH | - |
dc.date.accessioned | 2021-08-03T07:42:20Z | - |
dc.date.available | 2021-08-03T07:42:20Z | - |
dc.date.issued | 2002 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/1915 | - |
dc.description.abstract | Any small leakage in the submarines can lead to serious consecutive damages since it operates under high water pressure. Such leakage including damages on pipe and hull eventually incur human casualties and loss of expensive equipments as well as the loss of combat capabilities. In such cases, a decision-making system is necessary to respond immediately to the damages in order to maintain the safety or the survival of the submarine. So far, human decision has been the most important one based on personal experience, existing data, and any electronic information available. However, it is well recognized that such decisions may not be enough in certain emergency situations. The system that depends on only human experience may cause serious mistakes in devastating and scared situations. So it is necessary to have an automatic system that can generate responses and give advice the operator how to make decisions to maintain the survivability of the damaged vessel. In this paper, a knowledge-based decision support system for submarine safety is developed. The domain knowledge is acquired from the submarine design documents, design expertise, and interviews with operator. The knowledge consists of the responses regarding damage on pressure hull and piping system. Expert Elements are deduced to obtain the decision from the knowledge base, and for instance, the system makes recommendations on how the damages on hull and pipes decision and whether to stay in the sea or to blow. It is confirmed that developed system is well simulated to the real situation throughout sample applications. | - |
dc.format.extent | 11 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | SPRINGER-VERLAG BERLIN | - |
dc.title | A decision-support system to improve damage survivability of submarine | - |
dc.type | Article | - |
dc.publisher.location | 독일 | - |
dc.identifier.doi | 10.1007/3-540-48035-8_40 | - |
dc.identifier.scopusid | 2-s2.0-84943244510 | - |
dc.identifier.wosid | 000180978400041 | - |
dc.identifier.bibliographicCitation | DEVELOPMENTS IN APPLIED ARTIFICAIL INTELLIGENCE, PROCEEDINGS, v.2358, pp 403 - 413 | - |
dc.citation.title | DEVELOPMENTS IN APPLIED ARTIFICAIL INTELLIGENCE, PROCEEDINGS | - |
dc.citation.volume | 2358 | - |
dc.citation.startPage | 403 | - |
dc.citation.endPage | 413 | - |
dc.type.docType | Article; Proceedings Paper | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.subject.keywordAuthor | Decision-Support System | - |
dc.subject.keywordAuthor | Knowledge-Based System | - |
dc.subject.keywordAuthor | Survivability | - |
dc.subject.keywordAuthor | Submarine | - |
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