Building up multi-layered perceptrons as classifier system for decision support

This paper focuses on some application issues in multi-layered perceptrons researches. The following problem areas are discussed: (1) the classification capability of multi-layered perceptronsi (2) the self-configuration algorithm for facilitating the design of the neural nets' structure; and, finally (3) the application of the fast BP algorithm to speed up the learning procedure. Some experimental results with respect to the application of multi-layered perceptrons as classifier systems in the comprehensive evaluation of Chinese large cities are presented.