S.M. Taheri - Department MathematicalSciences, Isfahan University of technology, Isfahan ۸۴۱۵۶-۸۳۱۱۱, Iran
J Chachi - Dpartment of Mathematics, Statistics and Computer Sciences, Semnan University, Semnan ۳۵۱۹۵-۳۶۳,Iran

The problem of estimation of suspended load carried by a river flow is an important topic for many water resources projects. Conventional methods are based on the assumption of exact observations. But, in practice, a major source of natural uncertainty is due to imprecise measurements and/or imprecise relationships between variables. In this paper, by using Multivariate Adaptive Regression Splines (MARS) technique, a novel fuzzy regression model is introduced for imprecise response and crisp explanatory variables. The proposed fuzzy regression model is applied to forecast suspended load by discharge using a real hydrology data set. The estimation accuracy of the proposed method is compared with two current parametric fuzzy regression models, namely, fuzzy least-absolutes model and fuzzy least-squares model, indicating the advantages of the proposed model

Discharge; Hydrology; Multivariate Adaptive Regression Splines (MARS); suspended load