摘要
BP神经网络广泛应用于众多实际问题解决中,但是有一些缺点:容易陷入局部最小值,学习速度慢,计算精度低等。采用群智能算法优化的BP神经网络,可行性和实用性更强。本文对群智能算法中的遗传算法、蜂群算法、蚁群算法和萤火虫算法优化的BP神经网络应用进行分析和综述,对群智能算法优化BP神经网络的未来发展有着重要的参考价值。
BP neural network is widely used in many practical problems,but it has some disadvantages:easy to fall into local mini⁃mum value,slow learning speed,low calculation accuracy.BP neural network optimized by swarm intelligence algorithm is more feasible and practical.This paper analyzes and summarizes the application of BP neural network optimized by genetic algorithm,bee colony algorithm,ant colony algorithm and firefly algorithm,which has important reference value for the future development of swarm intelligence algorithm optimization BP neural network.
作者
杨洋
陈家俊
YANG Yang;CHEN Jia-jun(School of Electronics and Information Engineering West Anhui University,Lu’an 237012,China)
出处
《电脑知识与技术》
2020年第35期7-10,14,共5页
Computer Knowledge and Technology
基金
安徽省教育厅一般项目(KJ103762015B10)。
关键词
群体智能
BP神经网络
遗传算法
蜂群算法
蚁群算法
萤火虫算法
swarm intelligence
neural network
genetic algorithm
bee colony algorithm
ant colony algorithm
firefly algorithm
