The system for relieving students’ boring emotion in English learning based on fuzzy neural network

2021 ◽  
pp. 1-10
Author(s):  
Liuhui Yang ◽  
Xiuying Wu

The ability to perceive students’ emotions in real time is related to whether the description of the student’s state is accurate, and it is also related to whether the goal of achieving the students’ individual learning needs can be achieved. This paper studies the students’ boring emotion in English learning, and builds the recognition system of students’ boring emotion in English learning based on fuzzy neural network. Moreover, this paper combines the actual needs to construct the system function modules, and carries out the algorithm analysis and framework construction, and uses the mathematical modeling method to add the emotional factor to the English learner state modeling. In addition, according to the actual needs of the system constructed in this paper, the boring emotion of English learners is recognized. In addition, this paper designs experiments to verify the performance of the model, and analyze the system reliability from the theoretical perspective and the practical perspective. The experimental research results show that the model constructed in this paper meets the expected goals.

2012 ◽  
Vol 182-183 ◽  
pp. 1206-1210
Author(s):  
Li Hai Yao ◽  
Jie Xu ◽  
Hao Jiang

Automatic license plate recognition system is an intelligent surveillance system in traffic management and toll. Various image restoration methods have been proposed, but they are deficient in function approximation. Neural network has its unique advantages for its large-scale nonlinear dynamic characteristic, parallelism calculation, high robustness, strong capacity of self-adaptive, self-organization and self-learning. A novel license plate preprocessing technique based on fuzzy neural network has been proposed here, which is verified to be effective by the experiments.


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