Data mining with a simulated annealing based fuzzy classification system
Structural machine learning method—covering algorithm (CA) possesses faster speed, lower complexity and higher precision. But construction of the weight of the neurons for new center of sphere domain is usually given a manmade criteria, could not follow the distribution of samples to achieve the optimal solution. In this paper, a new constructive algorithm which combines the cross covering algorithm and Simulated Annealing is presented. It gets the covering center according to the search of the simulated annealing theory. The results show that the algorithm can reduce the number of coverings with higher degree of recognition accuracy.