A Novel Spatial Obstructed Distance by Dynamic Piecewise Linear Chaotic Map and Dynamic Nonlinear PSO

Spatial Clustering with Obstacles Constraints (SCOC) has been a new topic in Spatial Data Mining (SDM). Spatial Obstructed Distance (SOD) is the key to SCOC. The obstacles constraint is generally ignored in computing distance between two points, and it leads to the clustering result which is of no value, so obstructed distance has a great effect upon clustering result. In this paper, we propose a novel Spatial Obstructed Distance using Dynamic Piecewise Linear Chaotic Map and Dynamic Nonlinear Particle Swarm Optimization (PNPSO) based on Grid model to obtain obstructed distance, which is named PNPGSOD, it is not only simple and easy to actualize, but also convergent rapidly, the experimental results are provided to verify the effectiveness and practicability.