Modeling of thermal comfort in air conditioned rooms by fuzzy regression analysis

Thermal comfort is a vague and subjective term. Thermally comfortable is not only influenced by the physical environment but also influenced by individual feelings and perception, which is completely subjective and is generally expressed in linguistic terms. Traditional statistic approaches cannot handle these subjective aspects effectively. Fuzzy sets appear to be ideally suited for the modeling of this partially subjective system. To illustrate the effectiveness of fuzzy regression, two particularly fuzzy regression approaches were used to model thermal comfort. To obtain the needed data, experiments were first carried out. The influencing factors considered in the experiments included both the environment influences and the individual differences such as metabolic rate. The results are analyzed and the influence of individual feeling or perception plays an important role in the experimental results and in the modeling.

[1]  Phil Diamond,et al.  Fuzzy least squares , 1988, Inf. Sci..

[2]  P. Diamond,et al.  Extended fuzzy linear models and least squares estimates , 1997 .

[3]  H. Tanka Fuzzy data analysis by possibilistic linear models , 1987 .

[4]  حسن محمد الياس,et al.  Fuzzy Regression Analysis with an Application , 2006 .

[5]  A. Celmins Least squares model fitting to fuzzy vector data , 1987 .

[6]  J. Watada,et al.  Possibilistic linear systems and their application to the linear regression model , 1988 .

[7]  Ebrahim H. Mamdani,et al.  Fuzzy sets and applications: selected papers by L A Zadeh, R R Yager, S Ovchinikov, R M Tong, H T Nguyen (eds) John Wiley and Sons Inc, £45.85, ISBN 0 471 85710 6, 684pp , 1988, Knowl. Based Syst..

[8]  Ping-Teng Chang,et al.  Fuzzy least absolute deviations regression and the conflicting trends in fuzzy parameters , 1994 .

[9]  P. Fanger Calculation of Thermal Comfort, Introduction of a Basic Comfort Equation , 1967 .

[10]  A. Celmins Multidimensional least-squares fitting of fuzzy models , 1987 .

[11]  Junzo Watada,et al.  Possibilistic linear regression analysis for fuzzy data , 1989 .

[12]  Karl H.E. Kroemer,et al.  Ergonomics: How to Design for Ease and Efficiency , 1993 .

[13]  Ping-Teng Chang,et al.  A generalized fuzzy weighted least-squares regression , 1996, Fuzzy Sets Syst..

[14]  Sergei Ovchinnikov,et al.  Fuzzy sets and applications , 1987 .

[15]  A. Bárdossy Note on fuzzy regression , 1990 .

[16]  Tomio Jindo,et al.  A fuzzy logic analysis method for evaluating human sensitivities , 1995 .

[17]  Z Jianghong,et al.  An evaluation of comfort of a bus seat. , 1994, Applied ergonomics.

[19]  Georg Peters Fuzzy linear regression with fuzzy intervals , 1994 .

[20]  Zhao Rongyi Fuzzy comprehensive evaluation of thermal sensation in dynamic thermal environment , 1998 .

[21]  L. Zadeh,et al.  Fuzzy sets and applications : selected papers , 1987 .

[22]  Stephan A. Konz,et al.  Work Design: Industrial Ergonomics , 1983 .