A Big-Neuron Based Expert System
With a new way of knowledge representation and acquirement, inference, and building an expert system based on big-neurons composed of different field expert knowledge presented in this paper, the fundamental theory and architecture of expert system based upon big-neuron theory has thus been built. It is unnecessary to organize a large number of production rules when using big-neurons to build an expert system. The facts and rules of an expert system have already been hidden in big-neurons. And also, it is unnecessary to do a great quantity of tree searching when using this method to do logic reasoning. Machine can do self-organizing and self-learning.
Unable to display preview. Download preview PDF.
- 1.Mookerjee, V.S., Michael, V.M.: Sequential Decision Models for Expert System Optimization. IEEE Trans. Knowl. Data Eng. 15(5), 675–687 (2003)Google Scholar
- 4.Stephen, I.G.: Connectionist Expert Systems. Commun. ACM 47(2), 152–169 (2004)Google Scholar
- 6.Shi, Z.Z.: Neural Computing. The Publishing House of Ele. Industry, China (1994)Google Scholar
- 8.Tomsovic, K.: An Expert System Assisting Decision-Making of Reactive Power/Voltage Control. IEEE Trans. on Power Apparatus and Systems, PWRS 1, 195–201 (1996)Google Scholar
- 11.Li, T.: The Fundamental Theory of Big-Neuron. In: Proceedings of ICNNSP, pp. 382–386 (1995)Google Scholar
- 12.Li, T.: ONPL: A Neuron-Oriented Programming Language. High Tech. Letter 7, 56–59 (2001)Google Scholar