Dempster-Shafer based probabilistic fuzzy logic system for wind speed prediction

This paper proposes an improved probabilistic fuzzy logic system with Dempster Shafer structure (DS-PFLS) for wind speed prediction. The Dempster Shafer theory and 3 sigma results are integrated into probabilistic fuzzy logic system (PFLS) to address the complex derivation of the secondary probability density function and to eliminate the computational overload. The secondary probability density function based on the center of primary fuzzy membership in PFLS is proposed. Moreover, an improved Chicken Swarm Optimization (CSO) is developed for optimizing the related parameters of DS-PFLS. Simulations and comparisons based on the wind speed prediction demonstrate the effectivity and efficiency of the proposed method.