Extracting new information is one of the knowledge management ability yet difficult in environment which contains fuzzy information. For example, measuring a product's quality is an important task which normally requires visual inspection basis, and this grading is subject to expert knowledge and interpretation. Apparently, fuzzy information is inherently included in this evaluation and an appropriate tool is necessary to manage such information. Thus, to assist the uncertain situation, in this paper, a fuzzy regression is introduced to improve the extraction of attribute'sweight in a multi-attribute decision making. The proposed model will manage the linguistic assessment provided by evaluators in order to compute collective assessments about the product samples. The proposed model is applied to milled rice grading, as the quality inspection process requires a method to ensure product quality. We include simulation results and highlight the advantage of the proposed method in handling the existence of fuzzy information and managing the information which comes from such uncertain environment.
机构:Department of Econonics and Business Administration, Institute of Statistics and Mathematics, J.W. Goethe-University Frankfurt am Main, D-60054 Frankfurt am Main