Berlin Wu

Correlation coefficients are commonly found with crisp data. In this paper, we use Pearson’s correlation coefficient and propose a method for evaluating correlation coefficients for fuzzy interval data. Our empirical studies involve the relationship between mathematics achievement and other projects.

Purpose: – The purpose of this paper is to use soft computing technique and fuzzy statistical tool to evaluate people's performance on the marketing research and time management. Design/methodology/approach: – Through standardized measurement system, the authors come up with real-value data to satisfy not the current needs but data itself. This is when fuzzy classification stands out and highlights the area of in-between and undefined. Findings: – The proposed metric system helps the authors to assess the distance among trapezoidal fuzzy data. The index of efficiency between observed time and ideal time is also presented. Originality/value: – With the ranking of fuzzy sample, the authors can examine the decision process by non-parametric testing hypothesis.

Purpose: – The purpose of this paper is to investigate optimal decision methods under a cooperative situation in two-echelon logistic models. Design/methodology/approach: – The authors propose the optimal strategies of exporters in the three types of rival game behaviors: Stackelberg, Collusion, and Cournot, each of which provides the optimal decision for the duopolistic shippers and the oligopolistic forwarders in each scenario. Findings: – From the empirical studies the paper finds that among three scenarios, the oligopolistic treatment of forwarders’ actions demonstrates that Stackelberg behavior can carry out the maximum profit, and Collusion game can achieve the maximum profit for the shippers. Originality/value: – Proposed an optimal decision methods in two-echelon logistic models.

In real‐world applications, sometimes randomness and fuzziness may coexist. In facility‐location problems, the data expressed in natural language may contain vague information. We discuss the uncertainty included in demands in facility‐location problems. The uncertain demand is calledfuzzy demandin this paper. In the facility‐location model, the parameters of fuzzy demand are determined by calculating the estimated expected value of the fuzzy demand, which is obtained by using the estimated parameters of the underlying probability distribution function of the fuzzy data. Moreover, we propose a defuzzification formula of the fuzzy demand called therealization of fuzzy demand. The defuzzification formula of fuzzy demand comprises the upper bound and the lower bound of the fuzzy demand. Moreover, the error of the fuzzy demand is assessed as the mean absolute percentage error of the fuzzy demand. Empirical studies show that we can solve real‐life location problems by using the defuzzification formula of fuzzy demand and get higher profit in our facility‐location model than by using conventional methods. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

In the study, we developed a new model of fuzzy correlation and empirically examined the fuzzy correlation with student test scores in subjects of Chinese and Mathematics. Our sample comprised 419 Taiwanese students in the 12-year compulsory education. We applied fuzzy theory and conducted simulations with the data from Normal, Uniform, and Cauchy distributions to illustrate the efficiency of our proposed methods.

In this article, we will provide the definition of fuzzy mode, related characteristics, and proofs. By discussing these characteristics, data analysis, and explanation for this issue, we apply the soft computing techniques on human thought measurement and public's idea with a more appropriate way. In the conclusion, future experiments and further suggestions are presented.