A novel hybrid localization scheme for deep mine based on wheel graph and chicken swarm optimization

Abstract

Abstract This paper proposes a hybrid localization scheme for deep mine monitoring via wireless sensor network. The algorithm is designed for optimal accuracy as well as efficiency. A clustering method based on wheel graph theory is proposed to standardize the subnetwork quantity and reduce the complexity of subsequent chicken swarm optimization (CSO). The proposed scheme allows for the swift and simple transformation of clusters, which minimizes complexity among clusters and improves the localization precision. Simulation and performance analysis results show that the localization accuracy of the proposed CSO-W scheme is 26.4% higher than D3D-MDS and 17.1% higher than CSO.