Predictions using fuzzy regression models

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Regression analysis is a powerful statistical tool used by engineers to predict infrastructure condition. The primary goal of the regression analysis is to find a best fitted mathematical model, so that a dependent variable can be forecasted from independent variables. Essentially, ordinary regression analysis is used to handle crisp data rather than fuzzy (non-crisp) data obtained from expert's subjective judgments. Therefore, the use of conventional regression technique is inappropriate when the dependent variable (condition rating) is a non-crisp or discrete variable. An An illustrative example regarding the cost estimate of excavation construction was exemplified. The results demonstrate the capability of the model that can assist cost engineers to better assess construction costs.

Original languageEnglish
Title of host publicationProceedings of the 5th International Conference on Engineering Computational Technology
Publication statusPublished - 2006
Event5th International Conference on Engineering Computational Technology, ECT 2006 - Las Palmas de Gran Canaria, Spain
Duration: 2006 Sep 122006 Sep 15


Other5th International Conference on Engineering Computational Technology, ECT 2006
CityLas Palmas de Gran Canaria

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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