Multi-granules evaluation model through fuzzy random regression analysis

Various approaches and models are introduced to facilitate better information extraction and decision making. Granular computation is one of the approaches which provide ability to extract information granules which encompasses a collection of entities. A relationship is used to connect granule and levels and further forms information granule model. This study emphasizes information granulation in the fuzzy random based environment. Dealing with data containing fuzzy and random characteristic is complicated in some way though this kind of data are exist in real world application and requires proper handling. Thus, a fuzzy random based regression is introduced to improve the extraction of weight of granules in building a multi-granular decision making scheme. The proposed model is able to organize decision or preference provided by evaluators in order to compute collective assessments about the product samples that will be used by the decision maker to determine final decision. A numerical example shows the usability of the model and presents the advantage of the proposed method.