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Optimal Sensor Placement Based on QPSCO Algorithm


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Optimal Sensor Placement Based on QPSCO Algorithm
JIANG Ding-guo1ZHANG Yu-lin2JIAO Zhu-qing1XU Bao-guo1
1.School of Communication and Control Engineering,Jiangnan University,Wuxi 214122,China;
curve-fitting least-square principle quantum-behaved particle swarms cooperative optimization algorithm optimal placement of sensor
Focusing on the problem of the sensor placement,a scheme of optimal sensor placement based on quantum-behaved particle swarms cooperative optimization(QPSCO) algorithm is proposed.A two-layer framework with particle swarms cooperative optimization and a mutation parameter is introduced by the QPSCO algorithm for larger searching scale and quicker convergence.Moreover,the residual sum of squares in least-square principle is introduced into the fitness function to enhance the fitting precision of the sensor position curve.The optimal sensor placement is accomplished.This method of optimal sensor placement is applied into the soil information gathering system,and the test result demonstrates that this scheme,which not only brings better optimization effect than particle swarm optimization and quantum-behaved particle swarm optimization,but also has more ideal position fitting accuracy than genetic algorithm,is effective and feasible to sensor placement.


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Last Update: 2012-11-19