Applied Study Of Intelligent Decision-making System Based On Expert System And Artificial Neural Network

By taking"the application demonstration project of the intelligent agricultural information technology — demonstration area of Chongqing City"Which is financed by intelligent computer topic of national 863 (project index:863-306-ZD-05-03-F) as background, this paper has a deep analysis of an intelligent decision-making application system based on Expert System (ES) and Artificial Neural Network (ANN) .The paper analyzes the feature of ES and ANN which are the two active branches of intelligence technology. The function structure of intelligent decision-making application system of using the tomato planting as an example to propose basing on combining ES and ANN .In the paper about knowledge base, this article discussed the knowledge base of the neural-expert hybrid system in four parts: knowledge acquirement, knowledge representation, knowledge examining and knowledge correcting. And put forward a new method which integrated with ES technology and ANN technology to represent the knowledge At last, the article analyzed the consistency and integrality of knowledge base and introduces the examining algorithm and correcting algorithm.In inference engine of intelligent decision-making application system, meta-knowledge inference engine is applied to coordinate with quantitative inference, qualitative inference and ANN inference. Then basing the theory of certainty, a new uncertain reasoning model was introduced and this model was validated in the example of tomato. Then, the step of realization of the neural-expert hybrid expert system's inference engine was introduced. A diagnose method of diseases and insect pests base on module of neural network was presented and realized in this paper. Through the arrangement and collection of the symptoms of diseases and insect pest, a complex multi-layers structure model of the neural network, which is made up of lots of sub-network, was built taking the advantage of neural network theory. And put the network training and network simulating into reality by using MATLAB language...