Cloud mapping and membership cloud of mapping
云映射和映射隶属云*

In order to describe uncertainties and their variation between events, this paper proposed a concept of cloud mapping. For each element of definition domain, used a matched stochastic variable to convert it to a possible value space. Distribution features of the stochastic variable cluster in definition domain form feature functions, which indicated variation of uncertainties according to change of independent variable. This paper proposed a concept of membership cloud of mapping. Each element of definition domain has a cloud piece. All cloud pieces form membership cloud of mapping. Expected function, used entropy function, and hyper entropy function to describe variation of qualitative concept in the whole definition domain. This paper proposed algorithms for generating positive mapping cloud and reverse mapping cloud. Taking human memory law as an example, introduced effectiveness and possible application of proposed cloud mapping and mapping cloud.