Harnessing data mining to explore incident databases [An article from: Journal of Hazardous Materials]
Book Details
PublisherElsevier
ISBN / ASINB000RR7OLE
ISBN-13978B000RR7OL1
AvailabilityAvailable for download now
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from Journal of Hazardous Materials, published by Elsevier in . The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
Large numbers of incident related databases have been established in the last three decades. The majority of attempts to explore these data marts were trials to identify patterns via first glance into the datasets. This study investigated a subset of incidents from fixed facilities in Harris County, TX, extracted from the National Response Center database. By classifying the information into groups and using data mining techniques, interesting patterns of incidents according to characteristics such as type of equipment involved, type of chemical released and causes involved were revealed and further these were used to modify the annual failure probabilities of equipments.
Description:
Large numbers of incident related databases have been established in the last three decades. The majority of attempts to explore these data marts were trials to identify patterns via first glance into the datasets. This study investigated a subset of incidents from fixed facilities in Harris County, TX, extracted from the National Response Center database. By classifying the information into groups and using data mining techniques, interesting patterns of incidents according to characteristics such as type of equipment involved, type of chemical released and causes involved were revealed and further these were used to modify the annual failure probabilities of equipments.
