Evolving Additive Trees for Modeling Biochemical Systems

摘要：

This paper presents a hybrid evolutionary method for identifying a system of ordinary differential equations (ODEs) from the observed time series. In this approach, the tree-structure based evolution algorithm and particle swarm optimization (PSO) are employed to evolve the architecture and the parameters of the additive tree models for the problem of system identification. Experimental results on modeling biochemical system show that the proposed method is more feasible and effective than other related works.

关键词： Additive tree models Evolutionary Algorithms Ordinary differential equations Particle swarm optimization, Biochemical systems

作者: Yuehui Chen Bin Yang Yaou Zhao Qingfang Meng

作者单位: Computational Intelligence Lab,School of Information Science and Engineering,University of Jinan,Shandong,Jinan 250022,P.R.China

会议类型: 国际会议

会议名称: The 3rd International Symposium on Optimization and System Biology(第三届最优化与系统生物学国际会议 OSB09)

会议地点: 张家界

会议语种:英文

页码: 132-141

在线出版日期: 2009-09-20（万方平台首次上网日期，不代表论文的发表时间）