A new-style clustering algorithm based on swarm intelligent theory

Traditional clustering algorithms generally have some problems, such as the sensitivity to initializing parameter, difficulty in finding out the optimization clustering result and the validity of clustering. In this paper, a FSM and a mathematic model of a new-style clustering algorithm based on the swarm intelligence are provided. In this algorithm, the clustering main body moves in a three-dimensional space and has the abilities of memory, communication, analysis, judgment and coordinating information. Experimental results conform that this algorithm has many merits such as insensitive to the order of the data, capable of dealing with exceptional, high-dimension or complicated data. The algorithm can be used in the fields of Web mining, incremental clustering. economic analysis, oattern recognition, document classification and so on.

Traditional clustering algorithms generally have some problems, such as the sensitivity to initializing parameter, difficulty in finding out the optimization clustering result and the validity of clustering. In this paper, a FSM and a mathematic model of a new-style clustering algorithm based on the swarm intelligence are provided. In this algorithm, the clustering main body moves in a three-dimensional space and has the abilities of memory, communication, analysis, judgment and coordinating information. Experimental results conform that this algorithm has many merits such as insensitive to the order of the data, capable of dealing with exceptional, high-dimension or complicated data. The algorithm can be used in the fields of Web mining, incremental clustering, economic analysis, pattern recognition, document classification and so on.