학술논문
A SOC estimation method based on Improved Fuzzy Broad Learning System
Document Type
Conference
Author
Source
2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Chinese Association of Automation (YAC), 2022 37th Youth Academic Annual Conference of. :651-656 Nov, 2022
Subject
Language
Abstract
In this paper, FBLS is used as the base model and Grasshopper optimization Algorithm algorithm(GOA) is used to find the optimal initial weight of Fuzzy Broad Learning System(FBLS). On the basis of finding the initial center of membership function, K-means algorithm is improved by using local density and local probability theory to find the optimal initial clustering center, so that the algorithm can be more accurate. According to the disadvantage that Grasshopper optimization Algorithm(GOA) is not easy to converge and jump out of the global optimization, the algorithm is improved by using the sine cosine theory, and the algorithm search is more comprehensive by improving the parameter Rl. The experimental simulation shows that the error of the improved SC-GOA-FBLS is significantly lower than that of GOA-FBLS,PSO-BP and FBLS.