Optimization of membership function for fuzzy control based on genetic algorithm and its applications

1998 ◽  
Vol 2 (4) ◽  
pp. 295-300 ◽  
Author(s):  
Fei Shi ◽  
Fangjing Zheng
Author(s):  
Xiaojia Pang ◽  
Yuwen Ning

The advancement of science has made computer technology and the education industry more and more closely related, and the development of intelligent teaching systems has also opened a new path for classroom teaching. This paper studies the application of fuzzy control based on genetic algorithms in the intelligent psychology teaching system. Facing the complicated variables in the teaching process, the improved genetic algorithm can better realize dynamic teaching decisions through fuzzy control. This article aims to improve the quality of psychology classroom teaching, and develops an intelligent psychology teaching system based on the fuzzy control theory of genetic algorithm. Combined with the current development of fuzzy control theory, the problems existing in the intelligent teaching system are studied and analyzed, and they have been optimized and improved. This paper proposes a control algorithm based on a teaching management system. The algorithm can implement fuzzy control on student models, knowledge organization structure, intelligent test papers and teaching decision-making. While restoring the real teaching process, it can better realize teaching students in accordance with their aptitude and improve teaching. The intelligence of the system. According to the system test data, the proportions of the difficulty of the system’s automatic test paper are 30.1%, 51.6%, 18.3%, which are in line with the designer’s set expectation of 3 : 5:2, which shows the improved genetic algorithm. It can realize the intelligent volume group function very well.


2020 ◽  
Vol 39 (6) ◽  
pp. 8805-8812
Author(s):  
Zhihui He ◽  
Xiaofeng Li

During the COVID-19 epidemic period, it is essential to strengthen physical exercise and improve the health of the whole people. In this paper, based on genetic algorithm, a fuzzy control system is proposed to dynamically adjust the exercise ability of the bodybuilders under the comprehensive consideration of parameters. Through experiments and data processing, the system obtains bioelectric information related to heart rate, heart rate variability and muscle fatigue of the fitness people in the three states of not fatigue, moderate fatigue and extreme fatigue, establishes fuzzy membership function, and thus establishes personalized fitness information feedback control strategy to maintain moderate fitness intensity. By narrowing the gap between the predicted RPE value based on objective information and the measured RPE, the method provides a unified subjective and objective exercise intensity for the bodybuilders, effectively expands the time of aerobic exercise, and enhances the effect of aerobic exercise. In addition, in order to expand the scope of application of the exercise intensity control model, the service-oriented transformation is carried out to enable it to provide fitness content combinations of interest to fitness practitioners and instructors.


2013 ◽  
Vol 303-306 ◽  
pp. 1153-1157
Author(s):  
Yi Zong Dai ◽  
De Jun Miao

Based on the nonlinear of the photovoltaic device output power and the frequent changes in the work environment, a fuzzy controller with genetic algorithm was applied to maximum power point tracking (MPPT) of photovoltaic generation system. The problem of difference in the different interval of the maximum point was solved. It ensure that the system has a higher accuracy .By comparing the method of the fuzzy control and the method of fuzzy control with genetic algorithm through simulation , the result demonstrates the better control effect.


2018 ◽  
Vol 12 (4) ◽  
pp. 154-161 ◽  
Author(s):  
Javad Khodaei-Mehr ◽  
Samaneh Tangestanizadeh ◽  
Ramin Vatankhah ◽  
Mojtaba Sharifi

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