Intelligent Decision Model Based on Optimized Simulated Annealing Algorithm

Rough set theory can be applied to rule induction. The rough set theory approximates a concept by three regions, namely, the positive,boundary and negative regions. Because of making decision by rough set constructing model, cost of the decision should be considered, we will propose an optimized simulated annealing algorithm(OSAA),which is an optimized algorithm for a minimum cost attribute reduction. A heuristic approach combined with the coarse-grained parallel algorithm are proposed to solve the problem of optimization DTRS. Experiments designed for the optimization simulated annealing algorithm and adaptive learning method are in comparing with the running time and decision-making cost. The optimization representation can bring some new insights into the research on decision-theoretic rough set model.