A fuzzy goal regression model for the construction cost estimation of municipal waste incinerators

A comparative analysis of methods to represent uncertainty in estimating the cost of constructing wastewater treatment plants

“…To ®nd out the solution of fuzzy parameters, an equivalent linear programming model has to be solved (see Appendix I). However, the prediction accuracy of fuzzy linear regression model cannot always be guaranteed better than that of conventional least-squares regression models, although fuzzy regression allows the inclusion of expert knowledge or fuzzy information in the model in advance (Chang et al, 1996). Chang et al (1996) further proposed the fuzzy goal regression model in order to improve the performance in comparison to fuzzy linear regression outputs.…”

“…However, the prediction accuracy of fuzzy linear regression model cannot always be guaranteed better than that of conventional least-squares regression models, although fuzzy regression allows the inclusion of expert knowledge or fuzzy information in the model in advance (Chang et al, 1996). Chang et al (1996) further proposed the fuzzy goal regression model in order to improve the performance in comparison to fuzzy linear regression outputs. To further upgrade the capability of fuzzy goal regression analysis, this paper provides two revised fuzzy goal regression approaches (see Appendix II), which address the variations or uncertainties in a fuzzy regression analysis by a series of¯exible formulations in a model.…”

“…To further upgrade the capability of fuzzy goal regression analysis, this paper provides two revised fuzzy goal regression approaches (see Appendix II), which address the variations or uncertainties in a fuzzy regression analysis by a series of¯exible formulations in a model. But it still has to identify the most attractive model structure among alternatives using a fuzzy goal programming procedure (Chang et al, 1996). The following case study is prepared for a comparative analysis of these three methods representing various types of uncertainties involved in the cost estimation of constructing wastewater treatment plants.…”

“…This paper serves as a companion study of Chang et al (1996) and Wen and Lee (1999). It is designed to recast a well-known problem of construction cost estimation for both domestic and industrial wastewater treatment plants via a comparative framework.…”

“…On the other hand, many real world applications, using the fuzzy forecasting technique as a means, are worthy of further discussions. Typical examples include the use of fuzzy linear regression for the forecasting of computer sale in the market (Heshmaty and Kandel, 1985), for illustrating cellulose hydrolysis (Gharpuray et al, 1986), for explaining the potential of fuzzy regression application in hydrology (Barddossy et al, 1990), for construction cost analysis of municipal incinerators using the fuzzy goal regression model (Chang et al, 1996), and for construction cost analysis of wastewater treatment plants using fuzzy linear regression model (Wen and Lee, 1999). This practice may grow in importance in the future because of limited resources available as well as rapid economic and population growth in many countries.…”