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MPGA-Based Indoor Localization for Non Steady-State Gas Source
Qiuming Li,Zhigang Liu,Jinkuan Wang,Kai Cheng 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.11
Traditional gas source localization algorithms are usually based on gas steady-state diffusion model which ignores the factor of the time, it is difficult to meet the practical application conditions. In order to solve this problem, we propose an effective gas source localization method based multiple population genetic algorithm(MPGA) to estimate the location of gas-leakage source via wireless sensor network. In this paper, we first build a gas unsteady-state diffusion model without wind based on the gas diffusion theory, and then we transfer the gas source location problem into a global optimization problem with the measured information of sensor nodes. Finally, we use MPGA to solve the optimization problem and obtain the location of the gas source. The simulation results show that the proposed method can quickly obtain the location of the gas source, and has the higher positioning accuracy as compared with tradition localization algorithms.