Development of a Decision Support System for Chemical Accident
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Decision support systems (DSS) are used extensively in business to enable managers to make future decisions. Every business area requires a customized DSS. The uniqueness of each business area stems from various types of data requirements for decision-making processes. Therefore, the developer must analyze each industrial area for its particular requirements before designing a DSS. The back-end of a decision support system involves comprehensive modeling of the issues related to indexing and storing data. The data in the back-end are subjected to data-mining procedures, which form the engine for retrieval of relevant and accurate information to the decision-maker. These procedures form the basis for Knowledge Discovery in Databases (KDD). The front end of a DSS involves statistical and mathematical models to convert the data into information for the manager. The statistical functions to be employed for processing data depend upon the requirements of the decision-maker. These issues applied to the chemical accident data demand an innovative out-of-box methodology. This paper explores the development of an appropriate decision support system for chemical accident data. Taxonomy for indexing accident data and the design of a corresponding database model are established. Innovative data mining techniques are also explored. Finally, mathematical and statistical models are introduced for more effective processing of accident data.
SubjectDecision Support System
Sharma, Gaurav; Rogers, W.; Mannan, M.S. (2001). Development of a Decision Support System for Chemical Accident. Mary Kay O'Connor Process Safety Center; Texas &M University. Libraries. Available electronically from