Introducing knowledge into learning based on genetic programming

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@Article{Babovic:2009:JH,

• author = "Vladan Babovic",
• title = "Introducing knowledge into learning based on genetic programming",
• journal = "Journal of Hydroinformatics",
• year = "2009",
• volume = "11",
• number = "3-4",
• pages = "181--193",
• keywords = "genetic algorithms, genetic programming, empirical equations, hydraulics, sediment transport, strong typing, symbolic regression, units of measurement",
• ISSN = "1464-7141",
• URL = "http://www.iwaponline.com/jh/011/0181/0110181.pdf",
• DOI = "doi:10.2166/hydro.2009.041",
• size = "13 pages",
• abstract = "This work examines various methods for creating empirical equations on the basis of data while taking advantage of knowledge about the problem domain. It is demonstrated that the use of high level concepts aid in evolving equations that are easier to interpret by domain specialists. The application of the approach to real-world problems reveals that the use of such concepts results in equations with performance equal or superior to that of human experts. Finally, it is argued that the algorithm is best used as a hypothesis generator assisting scientists in the discovery process.",

}

Genetic Programming entries for Vladan Babovic

Citations