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。
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.
推理机设计采用启发式搜索，结合正向、反向及双向推理建立专家系统。
The elicitation search and integrated forward direction, reverse direction and bidirectional reasoning was adopted to set up expert system in reasoning machine design.
专家系统中的知识采用启发式表示，知识可以表示成确定性和不确定性知识。
The knowledge in the ES adopts the production systems, which can express the certain and uncertain knowledge.
专家系统中的知识采用启发式表示，知识可以表示成确定性和不确定性知识。
The knowledge in the ES adopts the production systems, which can express the certain and uncertain knowledge.
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