Fuzzy optimal control arithmetic was designed for each module, and an improved BP neural network was introduced to implement the fuzzy relation.

对每个控制模块设计了相应的模糊优化控制算法，并用改进的BP神经网络实现算法的模糊关系。

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The standard value of the tested software to pass the test was then obtained from the fuzzy control relation and fuzzy inference rules, thus quantifying the judgment for software to pass the test.

基于这种模糊控制关系和模糊推理规则，得到了被测软件通过测试的标准值，使测试通过的判定得以量化；

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The mechanism of the fuzzy predictive control is introduced briefly and how to established fuzzy predictive model base on the fuzzy relation and how to realize the model are introduced in details.

简单介绍了模糊预测控制系统的原理，详细介绍了如何建立基于模糊关系的模糊预测控制系统中的预测模型以及如何实现模糊预测控制的模糊预测模型。

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