An integrated approach for modelling of multivariate data based on statistical principles and neural networks
by Prasun Das
International Journal of Artificial Intelligence and Soft Computing (IJAISC), Vol. 2, No. 1/2, 2010

Abstract: For multivariate systems, empirical modelling using statistical methods is an issue in the presence of multicollinearity. Recently, neural networks provide a wide class of general-purpose, flexible non-linear non-parametric mapping, ignoring the fact of underlying data property. In this work, a composite system is designed to integrate the statistical principles of multivariate data, particularly multicollinearity, into the neural network architecture. The designed system is trained and validated with a simulated database based on the extent of correlation structure among the input variables. A real-life case with a large multi-dimensional system is illustrated under the proposed system.

Online publication date: Sun, 04-Apr-2010

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