Fuzzy assessment for sampling survey defuzzification by signed distance method

Since traditional sampling survey via questionnaire is difficult in reflecting interviewee’s incomplete assessment and uncertain thought, we use fuzzy sense of sampling to express the degree of interviewee’s feelings, and find that the result is closer to interviewee’s real thought. In this study, we propose two algorithms to do aggregative assessment for sampling survey by signed distance method with the linear order character of symmetric fuzzy linguistics instead of using previous centroid method. As the result that if the membership function of the triangular fuzzy number is not an isosceles triangle, then, based on the maximum membership grade principle, to defuzzify triangular fuzzy number by the signed distance is better than by the centroid method. The proposed fuzzy assessment method on sampling survey analysis is easily to assess the sampling survey and make the aggregative evaluation. Since the proposed model in this study is to measure the group evaluation, the final value is more objective than just one evaluator’s assessment. Moreover, if there is only one evaluator existing, the proposed model is also appropriate to assess.