The Design And Realization Of An Expert System Based On Neural Networks

At present, two systems in artificial intelligence that is developed well are expert system and artificial neural network. The former is based on symbol processing mechanism and the latter based on connection mechanism. Their applications not only make the fact that computer has intelligence become reality, but solve most problems in engineering. This paper combines the two methods and proposes a design of Expert System Based On Artificial Neural Network.The main contents of this paper as follows:1 .After deeply analyzing the current knowledge representation methods, the paper studies a knowledge representation method called binary production rule. The production rules are standardized into binary rules, each rule containing only two antecedents and one conclusion. After standardizing, knowledge can be easily stored in the ANN.2. Backpropagation model of the ANN is used in knowledge storage and the Leverberg-Marquardt algorithm based on numerical optimization is used in training the neural networks. As to the memory capability of the neural network, the paper propose to set up a system containing a couple of subnets, while each net storing an object and subnets working parallel.3. This paper analyzes the inference mechanism based on neural network and discusses two inference methods which are forward and backward inference. The forward inference algorithm starts from existing facts while the backwardinference starts from result fact.4. On the basis of the research mention above, the master plan and software development of the prototype system has been accomplished, the whole system mainly includes two parts: scheme design and software development. Relevant experiments have been accomplished to the system prototype, including knowledge storage and inference based on neural network. The experiment results show that the scheme and algorithms of system are usable and effective.