Symbolic and numerical regression: Experiments and applications

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@Article{davidson:2003:IS,

• author = "J. W. Davidson and D. A. Savic and G. A. Walters",
• title = "Symbolic and numerical regression: Experiments and applications",
• journal = "Information Sciences",
• year = "2003",
• volume = "150",
• pages = "95--117",
• number = "1-2",
• DOI = "doi:10.1016/S0020-0255(02)00371-7",
• URL = "http://www.sciencedirect.com/science/article/B6V0C-474DD2V-1/2/3368220198ea15f93a793594af73d8d1",
• keywords = "genetic algorithms, genetic programming, Least squares, Rule-based programming, Stepwise regression, Symbolic regression",
• abstract = "This paper describes a new method for creating polynomial regression models. The new method is compared with stepwise regression and symbolic regression using three example problems. The first example is a polynomial equation. The two examples that follow are real-world problems, approximating the Colebrook-White equation and rainfall-runoff modelling. The three example problems illustrate the advantages of the new method.",

}

Genetic Programming entries for J W Davidson Dragan Savic Godfrey A Walters

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