A Hybrid System with Regression Trees in Steel-Making Process

Mirosław Kordos , Marcin Blachnik , Marcin Perzyk , Jacek Kozłowski , Orestes Bystrzycki , Mateusz Gródek , Adrian Byrdziak , Zenon Motyka

Abstract

The paper presents a hybrid regresseion model with the main emphasis put on the regression tree unit. It discusses input and output variable transformation, determining the final decision of hybrid models and node split optimization of regression trees. Because of the ability to generate logical rules, a regression tree maybe the preferred module if it produces comparable results to other modules, therefore the optimization of node split in regression trees is discussed in more detail. A set of split criteria based on different forms of variance reduction is analyzed and guidelines for the choice of the criterion are discussed, including the trade-off between the accuracy of the tree, its size and balance between minimizing the node variance and keeping a symmetric structure of the tree. The presented approach found practical applications in the metallurgical industry.
Author Mirosław Kordos
Mirosław Kordos,,
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, Marcin Blachnik
Marcin Blachnik,,
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, Marcin Perzyk (FPE / IoMP)
Marcin Perzyk,,
- The Institute of Manufacturing Processes
, Jacek Kozłowski (FPE / IoMP)
Jacek Kozłowski,,
- The Institute of Manufacturing Processes
, Orestes Bystrzycki
Orestes Bystrzycki,,
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, Mateusz Gródek
Mateusz Gródek,,
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, Adrian Byrdziak
Adrian Byrdziak,,
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, Zenon Motyka
Zenon Motyka,,
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Pages222-230
Book Corchado Emilio, Kurzyński Marek, Woźniak Michał (eds.): Hybrid Artificial Intelligent Systems, Lecture Notes In Computer Science, no. 6678, 2011, Springer Berlin Heidelberg, ISBN 978-3-642-21218-5, 978-3-642-21219-2
Keywords in EnglishAlgorithm Analysis and Problem Complexity, Artificial Intelligence (incl. Robotics), Computation by Abstract Devices, Database Management, Information Storage and Retrieval, Information Systems Applications (incl.Internet)
URL http://link.springer.com/chapter/10.1007/978-3-642-21219-2_29
Score (nominal)4
Publication indicators WoS Citations = 8
Citation count*6 (2015-02-27)
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