Abstract:

In order to obtain the relatively minimal reduction of the attributes in a decisionmaking system, an attribute reduction algorithm is proposed based on immune algorithm. The core is joined initial population in the algorithm in order to accelerate capability. According to the dependability of decision attribute to the condition attribute and the condition attribute’s number of antibody, a new fitness function is defined. By the immune memory characteristics and the promoting and restraining function of antibody, it can maintain the individual’s diversity, and improve the global search ability of the algorithm, and avoid the local convergence, thus solves the minimal attribute reduction set. The experimental results show that the algorithm can find effectively and quickly the better minimal attribute reduction.

Key words: immune algorithm;rough set;attribute reduction