基于改进粒子群算法的精准农业无线传感器定位研究
|
摘要
为了提高精准农业无线传感器定位的精度,提出改进粒子群算法。首先建立精准农业无线传感器定位过程;接着对粒子群算法的惯性权重进行非线性优化,使得算法前期变化缓慢,后期变化较快,利于算法跳出局部而求得全局最优解;然后对粒子群规模采取收缩扩张控制,其判别结合粒子的聚集度、多样性函数,算法前期的收缩扩张系数值在较大的位置,后期应减慢速度以加强算法的局部搜索能力;最后建立定位误差与粒子适应度函数关系。实验仿真显示本文算法收敛性能较好,相比其他算法能有效地抑制测距误差对定位的影响,提高节点的定位精度。
In order to improve the positioning accuracy of precision agriculture wireless sensor, an improved particle swarm optimization(PSO) algorithm was proposed. Firstly, the positioning process of precision agriculture wireless sensor is established. Then, the inertia weight of particle swarm optimization is nonlinearly optimized, which makes the change of the algorithm slow in the early stage and fast in the later stage. Then, the size of the particle swarm is controlled by contraction and expansion, and its discrimination is combined with the aggregation degree and diversity function of the particles. In the early stage, the contraction and expansion coefficient of the algorithm is at a large position, and in the later stage, the speed should be slowed down to strengthen the local search ability of the algorithm. Finally, the relationship between positioning error and particle fitness function is established. The experimental simulation shows that the proposed algorithm has better convergence performance, and can effectively suppress the influence of ranging error on location and improve the positioning accuracy of nodes compared with other algorithms.
In order to improve the positioning accuracy of precision agriculture wireless sensor, an improved particle swarm optimization(PSO) algorithm was proposed. Firstly, the positioning process of precision agriculture wireless sensor is established. Then, the inertia weight of particle swarm optimization is nonlinearly optimized, which makes the change of the algorithm slow in the early stage and fast in the later stage. Then, the size of the particle swarm is controlled by contraction and expansion, and its discrimination is combined with the aggregation degree and diversity function of the particles. In the early stage, the contraction and expansion coefficient of the algorithm is at a large position, and in the later stage, the speed should be slowed down to strengthen the local search ability of the algorithm. Finally, the relationship between positioning error and particle fitness function is established. The experimental simulation shows that the proposed algorithm has better convergence performance, and can effectively suppress the influence of ranging error on location and improve the positioning accuracy of nodes compared with other algorithms.
引文
[1] 张增林,郁晓庆.土壤水分无线传感器网络节点设计与测试[J].中国农村水利水电,2012,(12):5-8.
[2] 韩红亮,缴锡云,王雪梅.蔬菜大棚墒情传感器垂向埋设位置研究[J].节水灌溉, 2017,(4):62-64.
[3] 秦宁宁,陈肯,孙文心.传感器网络中阈值Nesterov加速梯度下降定位方法[J].传感技术学报,2018,31(7):1 091-1 096.
[4] Yu Liu,Xiao Yi,You He.A novel centroid localization for wireless sensor networks[J].International Journal of Distributed Sensor Networks,2012,2012(2012):1-8.
[5] XueJun-xiao,Li Qing-bin,Liu Cheng-ming,et al.Parameterization of triangulated surface meshes based on constraints of distortion energy optimization[J].Journal of Visual Languages & Computing,2018,46(6):53-62.
[6] Yao Yong-lei,Xiong Nai-xue,Park Jong Hyuk,et al.Privacy-preserving max/min query in two-tiered wireless sensor networks[J].Computers & Mathematics with Applications,2013,65(9):1 318-1 325.
[7] Pedro Machado Manh?esde Castro,OlivierDevillers.Practical distribution-sensitive point location in triangulations[J].Computer Aided Geometric Design,2013,30(5):431-450.
[8] Cui Lai-zhong,Xu Chong,Li Geng-hui,et al.A high accurate localization algorithm with DV-Hop and differential evolution for wireless sensor network[J].Applied Soft Computing,2018,68(7):39-52.
[9] Ashanie Gunathillake,Andrey V.Savkin,Anura P.Jayasumana.Topology mapping algorithm for 2D and 3D Wireless Sensor Networks based on maximum likelihood estimation[J].Computer Networks,2018,130(15):1-15.
[10] 于晓升,王莹,孟亚男,等.基于IMM-IKF的无线传感器网络非视距节点定位方法[J].控制与决策,2018,33(6):1 069-1 074.
[11] Fang Xiao-wei,Ni Qin,Zeng Mei-lan.A modified quasi-Newton method for nonlinear equations[J].Journal of Computational and Applied Mathematics,2018,328(15):44-58.
[12] Sun Zi-wen,Liu Yu-hui,Li Tao.Attack localization task allocation in wireless sensor networks based on multi-objective binary particle swarm optimization[J].Journal of Network and Computer Applications,2018,112(15):29-40.
[13] Wang Tian-shu,Zhang Gong-xuan,Yang Xi-chen,et al.Genetic algorithm for energy-efficient clustering and routing in wireless sensor networks[J].Journal of Systems and Software,2018,146(11):196-214.
[14] SAVARESE C,RABAEY J,LANGENDOEN K.Robust positioning algorithms for distributed ad hoc wireless sensor network[C]//Proceedings of the USENIX Technical Annual Conference.Monterey:USEIX Press,2002:317-327.
[15] Sun Xue-mei,Zhang Yi-ming,Ren Xu,et al.Optimization deployment of wireless sensor networks based on culture-ant colony algorithm[J].Applied Mathematics and Computation,2015,250(1):58-70.
[16] 戴天虹,王硕.基于 BPSDV-Hop 的无线传感器网络节点定位算法[J].电子技术与软件工程,2018,(5):30-32.
[17] 彭越兮,徐蔚鸿,陈沅涛,等.改进量子粒子群算法的模糊神经网络水质评价[J].计算机工程与应用,2018,54(11):211-216.
[18] 卞国龙,黄海松,王安忆,等.基于PSO-BP算法的无线传感器网络定位优化[J].电讯技术,2017,57(2):139-144.
[19] 汪晗,成昂轩,王坤,等.无线传感器网络分布式迭代定位误差控制算法[J].电子与信息学报,2018,40(1):72-78.
[20] 庞先伟,左仁淑,王婷婷,等.基于IFOA优化DV distance 算法的无线传感器网络定位研究[J].现代电子技术,2017,40(13):22-25.
[2] 韩红亮,缴锡云,王雪梅.蔬菜大棚墒情传感器垂向埋设位置研究[J].节水灌溉, 2017,(4):62-64.
[3] 秦宁宁,陈肯,孙文心.传感器网络中阈值Nesterov加速梯度下降定位方法[J].传感技术学报,2018,31(7):1 091-1 096.
[4] Yu Liu,Xiao Yi,You He.A novel centroid localization for wireless sensor networks[J].International Journal of Distributed Sensor Networks,2012,2012(2012):1-8.
[5] XueJun-xiao,Li Qing-bin,Liu Cheng-ming,et al.Parameterization of triangulated surface meshes based on constraints of distortion energy optimization[J].Journal of Visual Languages & Computing,2018,46(6):53-62.
[6] Yao Yong-lei,Xiong Nai-xue,Park Jong Hyuk,et al.Privacy-preserving max/min query in two-tiered wireless sensor networks[J].Computers & Mathematics with Applications,2013,65(9):1 318-1 325.
[7] Pedro Machado Manh?esde Castro,OlivierDevillers.Practical distribution-sensitive point location in triangulations[J].Computer Aided Geometric Design,2013,30(5):431-450.
[8] Cui Lai-zhong,Xu Chong,Li Geng-hui,et al.A high accurate localization algorithm with DV-Hop and differential evolution for wireless sensor network[J].Applied Soft Computing,2018,68(7):39-52.
[9] Ashanie Gunathillake,Andrey V.Savkin,Anura P.Jayasumana.Topology mapping algorithm for 2D and 3D Wireless Sensor Networks based on maximum likelihood estimation[J].Computer Networks,2018,130(15):1-15.
[10] 于晓升,王莹,孟亚男,等.基于IMM-IKF的无线传感器网络非视距节点定位方法[J].控制与决策,2018,33(6):1 069-1 074.
[11] Fang Xiao-wei,Ni Qin,Zeng Mei-lan.A modified quasi-Newton method for nonlinear equations[J].Journal of Computational and Applied Mathematics,2018,328(15):44-58.
[12] Sun Zi-wen,Liu Yu-hui,Li Tao.Attack localization task allocation in wireless sensor networks based on multi-objective binary particle swarm optimization[J].Journal of Network and Computer Applications,2018,112(15):29-40.
[13] Wang Tian-shu,Zhang Gong-xuan,Yang Xi-chen,et al.Genetic algorithm for energy-efficient clustering and routing in wireless sensor networks[J].Journal of Systems and Software,2018,146(11):196-214.
[14] SAVARESE C,RABAEY J,LANGENDOEN K.Robust positioning algorithms for distributed ad hoc wireless sensor network[C]//Proceedings of the USENIX Technical Annual Conference.Monterey:USEIX Press,2002:317-327.
[15] Sun Xue-mei,Zhang Yi-ming,Ren Xu,et al.Optimization deployment of wireless sensor networks based on culture-ant colony algorithm[J].Applied Mathematics and Computation,2015,250(1):58-70.
[16] 戴天虹,王硕.基于 BPSDV-Hop 的无线传感器网络节点定位算法[J].电子技术与软件工程,2018,(5):30-32.
[17] 彭越兮,徐蔚鸿,陈沅涛,等.改进量子粒子群算法的模糊神经网络水质评价[J].计算机工程与应用,2018,54(11):211-216.
[18] 卞国龙,黄海松,王安忆,等.基于PSO-BP算法的无线传感器网络定位优化[J].电讯技术,2017,57(2):139-144.
[19] 汪晗,成昂轩,王坤,等.无线传感器网络分布式迭代定位误差控制算法[J].电子与信息学报,2018,40(1):72-78.
[20] 庞先伟,左仁淑,王婷婷,等.基于IFOA优化DV distance 算法的无线传感器网络定位研究[J].现代电子技术,2017,40(13):22-25.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |