文献类型：会议论文

英文题名：Artificial immune algorithm to function optimization problems

作者：Jing Zhang[1]

机构：[1] Basic Courses Dept., Beijing Union Univ., Beijing, China

第一机构：北京联合大学基础教学部

会议日期：27-29 May 2011

会议地点：Xi'an, China

语种：英文

外文关键词：artificial immune systems - learning (artificial intelligence)

摘要：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 today's 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, self-organization, 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.