Author(s): Mike Spiliotis; Luis Garrote
Linked Author(s): Luis Garrote de Marcos
Keywords: No Keywords
Abstract: In this work, an adaptive fuzzy based regression is proposed to include a non-constant behavior of the runoff as function of the precipitation. For high precipitation, beyond a fuzzy threshold, a conventional (crisp) relation between precipitation and runoff is established, while for low precipitation, a curve with different behavior must be derived. Between these curves and for a runoff range each curve holds to some degree. Therefore, it can be suggested that the proposed method emanates from the physical problem itself. Hence, a simplified Sugeno architecture scheme is established based on only two logical rules. The training process is achieved based on a combination between the Particle Swarm Optimization (PSO) method and the conventional least square method.
Year: 2022