Novel applications of data mining methodologies to incident databases

dc.contributorMannan, M. Sam
dc.creatorAnand, Sumit
dc.date.accessioned2006-08-16T19:12:58Z
dc.date.accessioned2017-04-07T19:51:57Z
dc.date.available2006-08-16T19:12:58Z
dc.date.available2017-04-07T19:51:57Z
dc.date.created2003-05
dc.date.issued2006-08-16
dc.description.abstractIncident databases provide an excellent opportunity to study the repeated situations of incidents in the process industry. The databases give an insight into the situation which led to an incident, and if studied properly can help monitor the process, equipment and chemical involved more closely, and reduce the number of incidents in the future. This study examined a subset of incidents from National Response Center??s Incident database, focusing mainly on fixed facility incidents in Harris County, Texas from 1990 to 2002. Data mining has been used in the financial and marketing arena for many decades to analyze and find patterns in large amounts of data. Realizing the limited capabilities of traditional methods of statistics, more robust techniques of data mining were applied to the subset of data and interesting patterns of chemical involved, equipment failed, component involved, etc. were found. Further, patterns obtained by data mining on the subset of data were used in modifying probabilities of failure of equipment and developing a decision support system.
dc.identifier.urihttp://hdl.handle.net/1969.1/3998
dc.language.isoen_US
dc.publisherTexas A&M University
dc.subjectData Mining
dc.subjectIncident
dc.subjectIncident Databases
dc.titleNovel applications of data mining methodologies to incident databases
dc.typeBook
dc.typeThesis

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