Adaptive Immune Genetic Algorithm for Tire Tread Pattern Pitch Parameters Optimization

被引:5
作者
Chen, Xia [1 ]
Chen, Lijun [1 ]
Chen, Yiqing [1 ]
Xiao, Wangxin [2 ]
机构
[1] Wuhan Univ Technol, Inst Mech & Elect Engn, Wuhan 430070, Peoples R China
[2] Wuhan Univ Technol, Minist Educ, Engn Res Ctr Transportat, Wuhan 430063, Peoples R China
来源
2009 THIRD INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL 1, PROCEEDINGS | 2009年
关键词
adaptive immune genetic algorithm; tire tread pattern; pitch parameter; mutiple parameters; optimization;
D O I
10.1109/IITA.2009.9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In order to reduce tire tread pattern noise, an adaptive immune genetic algorithm (AIGA) is presented to optimize tire pitch parameters in this paper. According to character of tire pattern, the algorithm defines crossover, mutation and reverse order operation to improve searching ability. The multiple parameters optimization is discussed in this paper. The simulation results indicate that compared with genetic algorithm (GA) and immune genetic algorithm (IGA), the convergence and the efficiency of AIGA are distinctly improved. The optimized results can reduce tread patterns noise level, which has been applicable to development of tire thread pattern.
引用
收藏
页码:52 / +
页数:2
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