Enhancing clustering quality of geo-demographic analysis using context fuzzy clustering type-2 and particle swarm optimization

摘要: Geo-Demographic Analysis, which is one of the most interesting inter-disciplinary research topics between Geographic Information Systems and Data Mining, plays a very important role in policies decision, population migration services distribution. Among some soft computing methods used for this problem, clustering popular because it has many advantages comparison with rests such as fast processing time, quality results memory space. Nonetheless, state-of-the-art algorithm namely FGWC low since was constructed on basis traditional fuzzy sets. In paper, we will present novel interval type-2 deployed an extension sets Interval Type-2 Fuzzy Sets to enhance FGWC. Some additional techniques context variable, Particle Swarm Optimization parallel are attached speed up algorithm. The experimental evaluation through various case studies shows that proposed method obtains better than best-known ones.