A clustering model based on colliding bodies optimization for analysis of seismic catalog

Nature has been the key source of inspiration for development of many heuristic optimization algorithm. In this manuscript a new clustering model is developed based on a recently developed nature inspired algorithm `Colliding Bodies Optimization (CBO)´. The CBO is based on the phenomenon of collision between bodies where each body try to occupy a convenient position in the search space. The proposed clustering model is applied to analyze the seismic activities of Japan catalog. If the number of clusters are known aprori with the help of seismologist then the proposed model provide accurate clustering performance with lower computation. Comparison with recently developed `fast density based clustering´ the proposed model provide equivalent clustering output for Japan catalog with lower computational time.