多值神经逻辑网络

Proceedings of the Twentieth International Symposium on Multiple-Valued Logic Pub Date : 1990-05-23 DOI:10.1109/ISMVL.1990.122658

L. Hsu, H. Teh, Sing-Chai Chan, K. Loe

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引用次数: 3

摘要

提出了两种可用于开发专家系统的网络。概率网络可用于预测类型的专家系统，而模糊网络更适合于帮助决策的专家系统。在这两种情况下，专家系统都可以在两种模式下运行。在正常模式下，规则由专家给出，权重赋值。在学习模式中，当系统被输入样本时，权重允许变化。

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Multi-valued neural logic networks

Two types of networks that are useful in developing expert systems are proposed. The probabilistic network can be used for predictive types of expert systems, whereas the fuzzy network is more suitable for expert systems that help in decision-making. In both cases, the expert system can operate in two modes. In the normal mode, rules are given by experts and weights are assigned values. In the learning mode, weights are allowed to vary while the system is fed with examples.<>

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来源期刊

Proceedings of the Twentieth International Symposium on Multiple-Valued Logic

CiteScore

1.90

自引率

0.00%

发文量