Abstrakt

Rule Generation in Automobile Sector to Identify Water Leakage Problem

Pragati Jain, Manisha Jain, Paheli Singhal

Rough Set approach has now been very widespread in the field of research. It has many applications almost in all areas related to business, banking, market research, information sciences, decision analysis, medical and many more. The paper presents the rough set approach as a tool to identify water leakage problem in automobiles. Decision and Conditional attributes play an important role in an information system. The approach generates sets of decision rules from data. Fundamentally the data representation with rough set theory is an information system that defines a discernibility matrix. Each entry consists of the set of attributes that can be used to discern between given objects. For every attribute an indiscernibility relation is defined. The basic idea of rough set is to construct approximation of sets using binary relations. The present paper explores the way of finding water leakage in front door cabin of an automobile by using minimal decision algorithm.