研究基于实例模型的模糊推理方法。
为提高夹具设计的敏捷性，提出了一种基于夹具功能分解的实例推理方法。
To improve agility of fixture design, a method of case reasoning based on decomposed fixture function was presented.
利用汽车发动机点火系统的故障实例验证了基于BP模型的神经网络故障诊断正向推理方法的有效性和可行性。
The validity and feasibility of the forward reasoning method for fault diagnosis based on BP neural networks are verified by the example of the faults in the ignition system of automobile engine.
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