Node Fault Detection Technology for Wireless Sensor Networks Based on RS-PSO-KELM Algorithm
The current node fault detection technology in wireless sensor networks is difficult to cope with the increasingly com-plex structure of wireless sensor networks.Therefore,a combination algorithm combining rough set,particle swarm optimization algo-rithm,and kernel extreme learning machine was studied and verified.The experimental results show that the root mean square error value of the research algorithm is 0.010 when the number of iterations is 5,0.008 when the number of iterations is 10,and 0.006 when the number of iterations is 50,all of which are lower than the comparison algorithm.The accuracy of the research algorithm on four datasets is basically higher than 85%,with a maximum of 98.51%.When applied to practical wireless sensor network node faults,the fault diagnosis accuracy is maintained at 98%~99%,and there is only one diagnostic error point.Overall,the algorithm proposed in the study has high performance in node fault diagnosis and verification of wireless sensor networks,and can be effectively applied in practical wireless sensor node fault diagnosis.