Research and Implementation of Fuzzy ISODATA Clustering Algorithm Based on Gene Expression Programming in Human Resource Management

Modifications are conducted in response to some disadvantages of ISODATA algorithm. With the combination of gene expression programming (GEP) nesting, an iterative self-organizing fuzzy clustering is constituted to realize calculation optimization. The convergence speed and clustering accuracy are evidently improved. Analysis of human resource management (HRM) is made by employing the modified algorithm, Results indicate that the new algorithm not only increases the convergence speed and the clustering accuracy, but fully uses the capability of global optimization of GEP algorithm and soft classification features of ISODATA, improving the degree of intelligence. In sum, ideal clustering effect is obtained.