Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7676
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dc.contributor.authorXu Kebinen_US
dc.contributor.authorWang Zhenyuanen_US
dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.date.accessioned2023-03-30T03:42:27Z-
dc.date.available2023-03-30T03:42:27Z-
dc.date.issued1998-
dc.identifier.citationProceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1998, Vol. 3, pp. 2326 - 2331en_US
dc.identifier.issn08843627-
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7676-
dc.description.abstractA new nonlinear multiregression model, Y = c+q·(w)∂f dμ+N(0,σ2), based on the Wang integral is developed to describe the multi-input single-output system. The model includes a non-additive set function μ, to describe the inherent interaction among the input attributes x1, x2, ..., xn. When the proper input-output data are available, by using the adaptive genetic algorithm, a precise estimated values of parameter c, q, ω, and μ of the regression model can be obtained. The output, Y, could be calculated by nonlinear multiregression using the values of known input attributes, x1, x2, ..., xn.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofProceedings of the IEEE International Conference on Systems, Man and Cyberneticsen_US
dc.titleUsing a new type of nonlinear integral for multi-regression: An application of evolutionary algorithms in data miningen_US
dc.typeConference Proceedingsen_US
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
Appears in Collections:Applied Data Science - Publication
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