二维正态云模型的单规则推理映射

Single rule reasoning mapping for the two dimensional normal cloud model

针对二维正态云模型在实现数据的定量输入到规则的定性推理、再到数据的定量输出的转换过程中,其输出与输入之间的映射区域存在的不确定性问题,通过构造3σ正态分布随机数,在输入云模型与输出云模型分别具有相同的熵参数和超熵参数的情况下,总结出二维正态云模型的单规则推理映射规律,指出该映射区域是一个发散区域,其大小不但与云模型的参数期望有关,而且还与参数熵和超熵有关,而最大离散系数则与期望无关,该结论可以作为二维正态云模型多规则映射研究的理论指导.

Due to the fact that the two-dimensional normal cloud model is used for conversion from the quantitative input of data to the qualitative rules of reasoning, and then to the quantitative output of data, the mapping of the region from the input to the output is very uncertain. By constructing the normal distribution random number with as the parameter, in the case of the input cloud model having the same entropy and hyper entropy as the output cloud model, some conclusions of the single rule of reasoning mapping for the two-dimensional normal cloud model were summed up. It was also pointed out that the mapping region is a divergent region, and the size of the area is not on- ly related to the cloud model parameter of the expected value, but also to the parameters of the entropy and hyper entropy. However, the maximum dispersion coefficient is not related to the parameter of the expected value. The conclusions can serve as a two-dimensional normal cloud model for the purpose of mapping more rules.