A new strategy for parameter estimation of dynamic differential equations based on NSGA II

Authors:
Yingzi Shi;Jiangang Lu;Qiang Zheng
Affiliations:
School of Education Science, Hangzhou Teachers College, Hangzhou, China;National Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China;National Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China
Venue:
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Year:
2006

Citing 3
Cited 1

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Abstract

A new strategy for parameter estimation of dynamic differential equations based on nondominated sorting genetic algorithm II (NSGA II) and one-step-integral Treanor algorithm is presented. It is adopted to determine the exact model of catalytic cracking of gas oil. Compared with those conventional methods, for example, quadratic programming, the method proposed in this paper is more effective and feasible. With the parameters selected from the NSGA II pareto-optimal solutions, more accurate results can be obtained.