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《Journal of Transcluction Technology》 2004-01
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Optimizing Cost of Redundant Multi-sensor Systems Using an Artificial Immune Algorithm

Yin Gui-liang (Electrical Engineering Department, Yanshan University, Qinhuangdao 066004, China)  
Using human immune system mechanisms, an artificial immune algorithm used for optimizing cost of redundant multi-sensor systems is presented. The artificial immune algorithm uses hyper-mutation to search local areas and receptor editing to escape from local minima. It is more suitable than simulated annealing and genetic algorithms for solving the problem that presents many local minima. Experimental results show the method is efficient.
【CateGory Index】: TP212
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