Evolutionary Modeling of Systems of Ordinary Differential Equations with Genetic Programming

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@Article{cao:2000:odeGP,

• author = "Hongqing Cao and Lishan Kang and Yuping Chen and Jingxian Yu",
• title = "Evolutionary Modeling of Systems of Ordinary Differential Equations with Genetic Programming",
• journal = "Genetic Programming and Evolvable Machines",
• year = "2000",
• volume = "1",
• number = "4",
• pages = "309--337",
• month = oct,
• keywords = "genetic algorithms, genetic programming, evolutionary modeling, system of ordinary differential equations, higher-order ordinary differential equation",
• ISSN = "1389-2576",
• URL = "http://www.ees.adelaide.edu.au/people/enviro/cao/2000-05.pdf",
• DOI = "doi:10.1023/A:1010013106294",
• size = "29 pages",
• abstract = "This paper describes an approach to the evolutionary modeling problem of ordinary differential equations including systems of ordinary differential equations and higher-order differential equations. Hybrid evolutionary modeling algorithms are presented to implement the automatic modeling of one- and multi-dimensional dynamic systems respectively. The main idea of the method is to embed a genetic algorithm in genetic programming where the latter is employed to discover and optimize the structure of a model, while the former is employed to optimize its parameters. A number of practical examples are used to demonstrate the effectiveness of the approach. Experimental results show that the algorithm has some advantages over most available modeling methods.",
• notes = "Article ID: 273810",

}

Genetic Programming entries for Hong-Qing Cao Li-Shan Kang Yu-Ping Chen Jingxian Yu

Citations