Estimation of Contamination Source by Using QPSO with Perturbation Operator

Abstract

Abstract: An improved quantum-behaved particle swarm optimization (QPSO) with perturbation operator was proposed and applied to solve the convection-diffusion inverse problem of estimating time-varying contamination source. Because the contamination source is time-dependent, the inverse problems are classified into function estimation problem. To transform the inverse problem to optimization problem, the nonlinear least square method was used. Meanwhile, Tikhonov regularization was used to stablize the solution with noisy measured data. And the regularization parameter was chosen by L-curve method. The simulation results tell that QPSO with perturbation operator outperforms QPSO and PSO. Moreover, tests over different views (regularization terms, noise level, sensor positions) were performed.

Key words: perturbation operator, quantum-behaved particle swarm optimization, contamination source estimation, partial differential equation

CLC Number:

TP399

Tian Na, Ji Zhicheng. Estimation of Contamination Source by Using QPSO with Perturbation Operator[J]. Journal of System Simulation, 2015, 27(7): 1628-1637.

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