基于VI-MFO的智慧乡村平台智能培养系统研究  

Research on intelligent cultivation system of intelligent village platform based on VI-MFO

作　　者：商竞 万珊[1] 苟文博 SHANG Jing;WAN Shan;GOU Wenbo(Xi’an Aeronautical Polytechnic Institute,Xi’an 710089,China;AVIC Xi’an Aircraft Industry(Group)Co.,Ltd.,Xi’an 710089,China)

机构地区：[1]西安航空职业技术学院,西安710089 [2]航空工业西安飞机工业(集团)有限责任公司,西安710089

出　　处：《自动化与仪器仪表》2024年第8期144-149,共6页Automation & Instrumentation

基　　金：西安航空职业技术学院校级智库,团队名称:航空城数字文旅与数字乡村研究中心(ZK23-01);陕西省教育科学“十四五”规划2022年度一般课题《新职教法背景下陕西高职电子商务专业助力乡村振兴路径研究与实践》(SGH22Y1628)。

摘　　要：为了提高智慧乡村平台智能培养系统信息传输的效率,提出一种基于VI–MFO算法的信息传输网络节点部署优化方法。研究首先从通信网络的全连通、通信能耗两个方面,建立网络节点最优部署的多目标评价模型。之后针对模型求解,提出一种改进的MFO算法,一方面通过引入全局扰动因子和互利因子,解决算法后期全局搜索能力下降且易陷入局部最优的问题;另一方面使用三维维诺图对网络节点的空间分布进行划分,将维诺图中各节点的权重引入改进MFO算法,设计了一种基于三维维诺图的引导式搜索算法,解决传统智能算法种群生成随机与搜索过程中无序的问题。结果表明,相较于原始MFO算法、SSA算法和BOA算法等经典群智能优化算法,改进MFO算法的性能得到了显著提高,在5个测试函数上的收敛结果都是最佳,寻优精度和寻优稳定性优越。基于VI-MFO算法对智慧乡村平台智能培养系统通信网络节点部署的仿真结果表明,相较于未结合三维维诺图的改进MFO算法,VI-MFO算法在实现通信节点的全连通的基础上,能耗成本得到了降低,求解耗时减少了3.04 s,证明了所提改进方法的有效性。In order to improve the smooth and efficiency of information transmission in intelligent cultivation system of smart village platform,an optimization method of information transmission network node deployment based on VI-MFO algorithm is proposed.Firstly,a multi-objective evaluation model for the optimal deployment of network nodes is established from the aspects of full connectivity and communication energy consumption.Then,an improved MFO algorithm is proposed for solving the model.On the one hand,global disturbance factor and mutually beneficial factor are introduced to solve the problem that the global search ability of the algorithm decreases and it is easy to fall into local optimal.On the other hand,the spatial distribution of network nodes is divided by using the three-dimensional Venot diagram,and the weight of nodes in the Venot diagram is introduced into the improved MFO algorithm.A guided search algorithm based on the three-dimensional Venot diagram is designed to solve the problem of random generation and disorder in the search process of traditional intelligent algorithms.The results show that compared with the original MFO algorithm,SSA algorithm and BOA algorithm,the performance of the improved MFO algorithm is significantly improved,and the convergence results on the 5 test functions are the best,and the optimization accuracy and stability are superior.The simulation results based on the VI-MFO algorithm for the communication network node deployment of the intelligent cultivation system of the intelligent village platform show that compared with the improved MFO algorithm without 3D Venot diagram,the VI-MFO algorithm achieves full connectivity of the communication nodes,reduces the energy consumption cost and the solving time by 3.04s,which proves the effectiveness of the proposed improved method.

关 键 词：智慧乡村 智能培养 维诺图 飞蛾扑火算法 全局扰动因子 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]