论文信息 - The Study of WSN Node Localization Method Based on Back Propagation Neural Network

The Study of WSN Node Localization Method Based on Back Propagation Neural Network

In order to cut down the localization accuracy problem of wireless sensor network (WSN), a novel node localization method is proposed with back propagation neural network (BPNN). At first, the calculation of node localization is presented by ranging interval and signal strength, and the parameters are rapid solving base on BPNN. Finally, a simulation experiment is conducted to study the influence key factor with NS2 and MATLAB. The results show that, compared other localization algorithm, this method has good suitability, and it could effectively reduce the localization error.

[1] Md. Rafiqul Islam,et al. A Secure Cross-Domain SIP Solution for Mobile Ad Hoc Network Using Dynamic Clustering , 2015, SecureComm.

[2] Lin Chen,et al. Research on Extreme Learning of Neural Networks: Research on Extreme Learning of Neural Networks , 2010 .

[3] Shi Long,et al. Self-Localization Systems and Algorithms for Wireless Sensor Networks , 2005 .

[4] Ying-Chun Bo,et al. On Structure Design for RBF Neural Network Based on Information Strength , 2012 .

[5] Ji Jin. Analysis of Real Solutions Number by Four-Anchor Node Localization for Sensor Networks , 2014 .

[6] Md. Rafiqul Islam,et al. A secure and resilient cross‐domain SIP solution for MANETs using dynamic clustering and joint spatial and temporal redundancy , 2017, Concurr. Comput. Pract. Exp..

[7] Deng Wan. Research on Extreme Learning of Neural Networks , 2010 .

[8] Kim-Kwang Raymond Choo,et al. A Domain-Based Multi-cluster SIP Solution for Mobile Ad Hoc Network , 2014, SecureComm.

[9] Yang Ya. Research on Intrusion Detection Based on Incremental GHSOM , 2014 .