Data Mining Using Unguided Symbolic Regression on a Blast Furnace Dataset

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Kommenda:evoapps11,

• author = "Michael Kommenda and Gabriel Kronberger and Christoph Feilmayr and Michael Affenzeller",
• title = "Data Mining Using Unguided Symbolic Regression on a Blast Furnace Dataset",
• booktitle = "Applications of Evolutionary Computing, EvoApplications 2011: {EvoCOMPLEX}, {EvoGAMES}, {EvoIASP}, {EvoINTELLIGENCE}, {EvoNUM}, {EvoSTOC}",
• year = "2011",
• month = "27-29 " # apr,
• editor = "Cecilia {Di Chio} and Stefano Cagnoni and Carlos Cotta and Marc Ebner and Aniko Ekart and Anna I Esparcia-Alcazar and Juan J. Merelo and Ferrante Neri and Mike Preuss and Hendrik Richter and Julian Togelius and Georgios N. Yannakakis",
• series = "LNCS",
• volume = "6624",
• publisher = "Springer Verlag",
• address = "Turin, Italy",
• publisher_address = "Berlin",
• pages = "274--283",
• organisation = "EvoStar",
• keywords = "genetic algorithms, genetic programming, Variable Selection, Data Mining, Blast Furnace, steel",
• isbn13 = "978-3-642-20524-8",
• DOI = "doi:10.1007/978-3-642-20525-5_28",
• abstract = "In this paper a data mining approach for variable selection and knowledge extraction from datasets is presented. The approach is based on unguided symbolic regression (every variable present in the dataset is treated as the target variable in multiple regression runs) and a novel variable relevance metric for genetic programming. The relevance of each input variable is calculated and a model approximating the target variable is created. The genetic programming configurations with different target variables are executed multiple times to reduce stochastic effects and the aggregated results are displayed as a variable interaction network. This interaction network highlights important system components and implicit relations between the variables. The whole approach is tested on a blast furnace dataset, because of the complexity of the blast furnace and the many interrelations between the variables. Finally the achieved results are discussed with respect to existing knowledge about the blast furnace process.",
• notes = "Part of \cite{DiChio:2011:evo_a} EvoApplications2011 held inconjunction with EuroGP'2011, EvoCOP2011 and EvoBIO2011",

}

Genetic Programming entries for Michael Kommenda Gabriel Kronberger Christoph Feilmayr Michael Affenzeller

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