Fuzzy sets and applications
Least squares model fitting to fuzzy vector data
Fuzzy Sets and Systems
Fuzzy data analysis by possibilistic linear models
Fuzzy Sets and Systems - Fuzzy Numbers
Information Sciences: an International Journal
Possibilistic linear systems and their application to the linear regression model
Fuzzy Sets and Systems
Fuzzy Sets and Systems
Fuzzy linear regression with fuzzy intervals
Fuzzy Sets and Systems
A generalized fuzzy weighted least-squares regression
Fuzzy Sets and Systems
Information Sciences: an International Journal
Soft Computing and Learning Techniques in the Modeling of Humanistic Systems
International Journal of Artificial Life Research
Fuzzy regression analysis: An application on tensile strength of materials and hardness scales
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
| Hi-index | 0.98 |
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.