Applying a Flexible Fuzzy Adaptive Regression to Runoff Estimation

Environmental Sciences Proceedings

article

Mike Spiliotis¹  Luis Garrote² 

[1] Department of Civil Engineering, School of Engineering, Democritus University of Thrace;Department of Civil Engineering: Hydraulics, Energy and Environment, Universidad Politécnica de Madrid

关键词: fuzzy IF-THEN rules;    particle swarm optimization (PSO);    least square method;    fuzzy regression;    runoff estimation;   

DOI  :  10.3390/ECWS-7-14308

来源: mdpi

【 摘 要 】

A smart, flexible, fuzzy-based regression is proposed in order to describe non-constant behavior of runoff as a function of precipitation. Hence, for high precipitation, beyond a fuzzy threshold, a conventional linear (precise) relation between precipitation and runoff is established, while for low precipitation, a curve with different behavior is activated. Between these curves and for a runoff range, each curve holds to some degree. Hence, a simplified Sugeno architecture scheme is established on few logical rules. Alternatively, the model can be enhanced by using a combination between the fuzzy linear regression of Tanaka and the aforementioned simplified Sugeno architecture. The training process is achieved based on the Particle Swarm Optimization (PSO) method.

【 授权许可】

Unknown