Artificial Immune Algorithm to Function Optimization Problems
Optimization problems abound in the scientific research and engineering applications in various fields, the optimization method has important theoretical and practical value. The existence of the traditional shortcomings of optimization methods, in todays mass production application is limited. Multidisciplinary research to solve the optimization problem provides a new approach to biological intelligence or natural phenomena based on new intelligent optimization algorithms and applications in the study have shown excellent performance, the modern intelligent algorithms has become a new field of artificial intelligence research focus. Artificial immune optimization algorithm is an imitation of biological function of the immune system an intelligent way, providing a similar immune system noise tolerance, non-teacher learning, selforganization, memory and other evolutionary learning mechanism to solve the complex problems of the new distributed program, compared to other intelligent optimization algorithm has a high success rate optimization, individual diversity and good.
immune algorithm optimization intelligencecomputation
Jing Zhang
Basic Courses Department Beijing Union University Beijing, China
国际会议
2011 International Conference on System Modeling and Optimization(ICSMO 2011)(2011年系统建模与优化国际会议)
贵阳
英文
102-105
2011-01-26（万方平台首次上网日期，不代表论文的发表时间）