Research On Application Of Data Mining In Intelligent Decision Support System

Intelligent decision support system is a kind of new type information system, which has been born with the artificial intelligence and traditional decision support system. Data mining is up to logic reasoning, it is located in influence space of the intelligent decision support system, so data mining is the most important status in the intelligent decision support system.In the practical application, because data mining effect is mostly decided by data mining algorithm. So author give three kinds of improved data mining algorithm. The first, Subjective Bayesian Network Algorithm Based On Non-deterministic Knowledge: Bayesian network is a kind of directed acyclic graph to explain probability relation Subjective bayesian network algorithms based on non-deterministic knowledge are presented in this paper, and this algorithms have been realized in the system of repository, this algorithms can get rapid steady and precise reasoning from non-deterministic knowledge. The second, Genetic and Simulated Annealing Algorithm Based on Grid(GSGA):in order to increate the popularity and diversity of individuals, the GSGA can produces chromosomes with grid. The Simulated Annealing Algorithm act on the choice operator the crossover operator the mutation operator at the same time, so which can boost up self-adaptability of the simple Genetic Algorithm. The third, Evolution Initialization Connection Weights of the BP neural network based on the GSGA: the Algorithm has excellent capability of pattern-classification.Finally, author has realized the automatic model choice in the intelligent decision support system based on data mining algorithm and validated the front-mention algorithms.