Open AccessFuzzy BP neural network in radar intelligence quality evaluation
Author(s) -
Renzheng Liu,
Xiongfei Fan,
Zhijun Wang,
Wei Yue,
Kangsheng Tian
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1601/3/032018
Subject(s) - radar , artificial neural network , backpropagation , artificial intelligence , fuzzy logic , computer science , computational intelligence , quality (philosophy) , data mining , machine learning , telecommunications , philosophy , epistemology
This paper presents a novel approach of radar station intelligence quality evaluation which based on fuzzy Backpropagation neural network (BPNN). Firstly, the index system of the radar station intelligence quality evaluation is established according to the analysis of the process, the characteristics, and the main influencing factors of the radar station intelligence production. And then the factor set, comment set and the membership matrix are structured, the fuzzy BPNN for evaluating the quality of the radar station intelligence is designed referring to the index system. Finally, the experiment shows that the accuracy and stability can be improved effectively by using fuzzy BPNN to evaluate the radar station intelligence quality