Attribute Reduction Method and Its Application using Bat Algorithm and Rough Sets

Abstract

Attributes reduction is one of the important key in knowledge discovery. In order to find the effective methods of minimum attribute reduction and its application in data processing and analysis, an attribute reduction method by using bat algorithm and rough sets can be proposed by combining intelligent bat optimization algorithm with the rough sets. This method uses the attribute dependency to calculate the attribute core, combining the optimization of bat algorithm towards the attribute reduction to get the smallest attribute reduction. In the analyzation of criminal information, it will be applied to analyze the main influence factors of criminal behavior and carry out experimental verification. From the experimantal results, we found that this method is feasible and effective. By analysing the criminal behavior, the pattern of criminal characteristic will be discovered and this helps us to achieve the goal of criminal prevention and improve the police efficiency in handling cases.