We introduce a new way of computation of time dependent partial differential equations using hybrid method FEM in space and FDM in time domain and explicit computational scheme. The key idea is quick transformation of standard basis functions into new simple basis functions. This new way is used for better computational efficiency. We explain this way of computation on an example of elastodynam...

We consider time-harmonic scattering by penetrable polygonal obstacles in 2D. We present a boundary element method (BEM) based on a hybrid numerical-asymptotic (HNA) approximation space built from oscillatory basis functions. The basis functions are carefully chosen to capture the leading order terms in the highfrequency asymptotic behaviour of the boundary solution. Numerical experiments sugge...

In this paper we describe a new method for learning hybrid Bayesian network models from data. The method utilizes a kernel density estimator, which is in turn “translated” into a mixture of truncated basis functions-representation using a convex optimization technique. We argue that these estimators approximate the maximum likelihood estimators, and compare our approach to previous attempts at ...

We propose a hybrid method for forecasting the wind speed. The wind speed data is first decomposed into intrinsic mode functions (IMFs) with empirical mode decomposition. Based on the partial autocorrelation factor of the individual IMFs, adaptive methods are then employed for the prediction of IMFs. Least squares-support vector machines are employed for IMFs with weak correlation factor, and a...

In this article a method is presented to find systematically the domain of attraction (DOA) of hybrid non-linear systems. It has already been shown that there exists a sequence of special kind of Lyapunov functions Vn in a rational functional form approximating a maximal Lyapunov function VM that can be used to find an estimation for the DOA. Based on this idea, an improved method has been deve...

Knowledge extraction process poses certain problems like accessing sensitive, personal or business information. Privacy invasion occurs owing to the abuse of personal information. Hence privacy issues are challenging concern of the data miners. Privacy preservation is a complex task as it ensures the privacy of individuals without losing the accuracy of data mining results. In this paper, fuzzy...

In many real-world applications, various optimization problems with conflicting objectives are very common. In this paper we employ Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), a newly developed method, beside Tabu Search (TS) accompaniment to achieve a new manner for solving multi-objective optimization problems (MOPs) with two or three conflicting objectives. This i...

Queries containing aggregate functions o f e n combine multiple tables through join operations. We call these queries "Aggregate-Join" queries. In parallel processing of such queries, it must be decided which attribute to be used as a partitioning attribute, particularly join attribute or group-by attribute. Based on the partitioning attribute, we discuss three parallel aggregate-join query pro...

Image reconstruction from projections is a key problem in medical image analysis. In this paper, we cast image reconstruction from projections as a multi-objective problem. It is essential to choose some proper objective functions of the problem. We choose the square error, smoothness of the reconstructed image, and the maximum entropy as our objective functions of the problem. Then we introduc...