摘要
在规模化农机作业过程中,由于农机作业信息发布滞后和农机资源调度不合理,会造成农机作业效率低下的问题,特别是在农忙时节,会影响农作物的收割效果。为了提高农机作业效率,往往需要具备大规模的农机调度网络系统,以对农机资源进行合理的分配。农忙时网络系统使用的时间比较集中,为了不耽误作业调度系统的顺利运行,网络安全问题不容忽视;而农机调度网络系统的数据较为庞大,想要对其进行网络态势安全评价需要高效的处理算法。为此,将粒子群优化的神经网络算法引入到了农机调度网络安全态势评价过程中,并对其可行性和可靠性进行了验证。实验结果表明:采用粒子群优化的神经网络算法对于网络安全评价的效率较高,可以满足农机网络调度系统网络安全态势评价的需要。
In the process of large-scale agricultural machinery operation,due to the lag of the information release of agricultural machinery operation and the unreasonable scheduling of agricultural machinery resources,it will cause the low efficiency of agricultural machinery operation,especially in the busy season,which will affect the harvest effect of the crops.Therefore,in order to improve the efficiency of agricultural machinery operation,a large-scale agricultural machinery dispatching network system is often needed to allocate the agricultural machinery resources reasonably.The time of the use of the busy time network system is concentrated.In order not to delay the smooth operation of the operation scheduling system,the network security problem can not be ignored,and the agricultural machinery dispatching network is not allowed to be ignored.The data of the system are relatively large,so we need an efficient algorithm to evaluate the network situation security.In this study,the neural network algorithm of particle swarm optimization is introduced to the security situation evaluation process of agricultural machinery dispatching network,and its feasibility and reliability are verified.The experimental results show that the neural network algorithm using particle swarm optimization is more efficient for network security evaluation and can meet the adjustment of agricultural machinery network.The needs of the network security situation evaluation of the degree system.
作者
江楠
蔡增玉
张建伟
Jiang Nan;Cai Zengyu;Zhang Jianwei(Zhengzhou University of Light Industry,Zhengzhou 450002,China)
出处
《农机化研究》
北大核心
2020年第1期222-226,共5页
Journal of Agricultural Mechanization Research
基金
河南省科技攻关项目(172102210059)
关键词
粒子群优化
神经网络
农机调度
网络安全
作业效率
particle swarm optimization
neural network
agricultural machinery scheduling
network security
operational efficiency
