The parallelism, distribution and capability of learning of neural net heuristics provide a new way for knowledge acquisition, knowledge representation and uncertainty reasoning in expert systems.
神经元网络启发式的并行、分布特征和可学习性为专家系统的知识表达和获取、不确定性推理提供了新的途径。
Systems can learn knowledge and perform reasoning under the uncertainty environment automatically.
使得系统能够在不确定的环境中自动地进行学习和推理。
This paper develops an expert system for Electrocardiogram diagnosis. Its uncertainty reasoning with weight is based on the experience and specialty knowledge of experts.
本文以领域专家的理论知识和经验知识为基础，采用一加权不确定性推理方法，建立了一个心电诊断专家实验原型系统。
This paper develops an expert system for Electrocardiogram diagnosis. Its uncertainty reasoning with weight is based on the experience and specialty knowledge of experts.
本文以领域专家的理论知识和经验知识为基础，采用一加权不确定性推理方法，建立了一个心电诊断专家实验原型系统。
应用推荐