In sensory data fusion and integration consideration, sensor independence i s a common assumption. In this paper, we demonstrated the impact of including dependent information in sensory data combination process. The team consensus approach based on information entropy can improve the measurement accuracy remarkably. The major benefits of the approach are (a) the simple linear combination of th...

1 Abstract In this paper we present an application of predictive modular neural networks (PREMONN) to short term load forecasting. PREMONNs are a family of probabilistically motivated algorithms which can be used for time series prediction, classification and identification. PREMONNs utilize local predictors of several types (e.g. linear predictors or artificial neural networks) and produce a f...

This study estimates the influence of proximity to water bodies and park amenities on residential housing values in Knox County, Tennessee, using the hedonic price approach. Values for proximity to water bodies and parks are first estimated globally with a standard ordinary least squares (OLS) model. A locally weighted regression model is then employed to investigate spatial nonstationarity and...

Motivation: Gene expression microarray data sets often contain missing expression values. Robust missing value estimation methods are needed since many algorithms for gene expression analysis require a complete matrix of gene array values. In this paper, imputation methods based on the least squares and cluster structure are proposed to estimate missing values in the gene expression data, which...

An identification method is described to determine a weighted combination of local linear state space models from input and output data. Normalized radial basis function are used for the weights, and the system matrices of the local linear models are fully parameterized. By iteratively solving a nonlinear optimization problem, the centers and widths of the radial basis functions and the system ...

After a short introduction of a new nonconforming linear finite element on quadrilaterals recently developed by Park, we derive a dual weighted residual-based a posteriori error estimator (in the sense of Becker and Rannacher) for this finite element. By computing a corresponding dual solution we estimate the error with respect to a given target error functional. The reliability and efficiency ...

! A_CU-run6: local feature alone – average fusion of 3 SVM classification results for each concept using various feature representation choices. ! A_CU-run5: linear weighted fusion of A_CU-run6 with two grid-based global features (color moment and wavelet texture). ! A_CU-run4: linear weighted fusion of A_CU-run5 with a SVM classification result using detection scores of CU-VIREO374 as features...

Decision analysis can be defined as a set of systematic procedures for analysing complex decision problems. Differences between the desired and the actual state of real world geographical system is a spatial decision problem, which can be approached systematically by means of multi-criteria decision making. Many real-world spatially related problems give rise to geographical information system ...