现代电子技术2024，Vol.47Issue(24)：81-87,7.DOI:10.16652/j.issn.1004-373x.2024.24.013
基于ARINC661和遗传融合的手势识别算法研究
Research on gesture recognition algorithm based on ARINC661 and genetic fusion
孙森然 1程金陵 2黄素娟1
作者信息
- 1. 上海大学 通信与信息工程学院,上海 200444
- 2. 中国商飞 上海飞机设计研究院,上海 201210
- 折叠
摘要
Abstract
Traditional gesture recognition algorithms are usually affected by complex gesture patterns and noise interference,which leads to limited accuracy and does not conform to avionics system specifications.Therefore,an ant colony non-dominated sorting genetic algorithm-back propagation neural network conforming to ARINC661 specifications is proposed.The ant colony optimization(ACO)algorithm was used to optimize the initial population,and the third generation non-dominant sorting genetic algorithm was used to select the next generation individuals to preserve the diversity of the population.The mutation and crossover strategy after ACO and the population optimization update strategy are introduced to improve the convergence speed of the algorithm,and the weight and threshold of the neural network are optimized globally to improve the estimation accuracy and the robustness of the gesture recognition system.The experimental results show that,in comparison with existing algorithms,this algorithm can significantly increase the accuracy and convergence speed,and reduce the average standard error,providing an effective solution to the problem of insufficient gesture recognition precision in avionics systems.关键词
ARINC661/非支配排序遗传算法/手势识别/蚁群优化算法/BP神经网络/变异策略Key words
ARINC661/non-dominated sorting genetic algorithm/gesture recognition/ant colony optimization algorithm/BP neural network/variation strategy分类
信息技术与安全科学引用本文复制引用
孙森然,程金陵,黄素娟..基于ARINC661和遗传融合的手势识别算法研究[J].现代电子技术,2024,47(24):81-87,7.
