discretization methods
Validating the Effect of Different Discretization Methods for Redic K Prototype Clustering Algorithm
... data discretization methods. The purpose of discretization is to transfer the continuous attributes for into the categorical attributes for better performance of clustering ...the ...
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Discretization methods for control systems design
... This said, some conclusions can be drawn. For large sampling periods, it has been demonstrated that the bilinear transformation is totally unacceptable as a method of discretization. Further, the difficulties in ...
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Strong-stability-preserving Hermite – Birkhoff time discretization methods combining k-step methods and explicit s-stage Runge–Kutta methods of order 5
... Hermite–Birkhoff methods, HB(k,s, p) , of orders p = ...-step methods with s -stage RK methods of order ...HB methods of order p have also been found on ...well–known methods of the ...
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IFISS : a computational laboratory for investigating incompressible flow problems
... This time, using higher-order elements does not improve the asymptotic conver- gence rate, and both discretization methods have exactly the same rate of convergence. To emphasize the importance of the ...
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Feature Selection Algorithm with Discretization and PSO Search Methods for Continuous Attributes
... Abstract— Discretization plays a significant role during the transformation of continuous attributes into discrete values in the pre-processing step in data mining, significant attention in the machine learning ...
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A novel approach to determine two optimal cut-points of a continuous predictor with a U-shaped relationship to hazard ratio in survival data: simulation and application
... common discretization methods in survival data and meet the needs of finding optimal cut-points for a continuous predictor that has a U-shaped relationship with survival outcomes, we propose a new approach ...
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A successive iterative approach for two dimensional nonlinear Volterra-Fredholm integral equations
... numerical methods have been developed over the years to tackle them, such as time collocation and time discretization methods [6, 15], trapezoidal Nystrom method [11], Adomian decomposition method ...
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HCAIM: A Discretizer for the Hierarchical Classification Scenario Applied to Bioinformatics Datasets
... (EW) methods were ran using, for each attribute, the same number of intervals chose by ...reference methods used in the comparative ...all discretization methods are statistically ...
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Multilevel Monte Carlo for stochastic differential equations with small noise
... Carlo methods combined with discretization methods tailored to the small noise setting [10, 9], and (ii) multilevel Monte Carlo methods combined with Euler-Maruyama ...
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MCAIM: Modified CAIM Discretization Algorithm for Classification
... six discretization methods for seven different data ...six discretization methods, Equal-width, equal-count and standard deviation are unsupervised discretization algorithms ...
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Operator Splitting Method for Coupled Problems:Transport and Maxwell Equations
... We present a coupled model based on Maxwell and Transport equations, that can be applied for simplified transport model for an ionized gaseous species in a PECVD reator. Based the different scale models, we have included ...
13
Graph clustering-based discretization of splitting and merging methods (GraphS and GraphM)
... univariate methods discretize only a single attribute at a time and do not consider interactions among attribute, may lead to important information loss [3] and not getting a global optimal result ...variate ...
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Galerkin discretizations of 4th order in space and time for the Convection-Diffusion-Reaction (CoDiRe) equation
... mesh methods, so that these methods often have difficulties in changing the spatial mesh from time step to time ...semi- discretization in time, allows a fully adaptive integration of time dependent ...
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Error analysis of variational discretization solving temperature control problems
... element methods, namely, the h-methods (mesh refinement), the p-methods (order enrichment), the r- methods (mesh redistribution) and the hp-methods (the combination of h-method and ...
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A class of quasi variable mesh methods based on off step discretization for the numerical solution of fourth order quasi linear parabolic partial differential equations
... numerical methods for finding ap- proximate solutions to these equations are of great ...numerical methods available to approximate a fourth-order PDE, such as the finite element method, spline collocation ...
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European and American put valuation via a high-order semi-discretization scheme
... It is known that in finance [15], a put or put option is a stock market device which gives the owner a right, but not the obligation, to sell an asset, at a specified price (the strike), by a predetermined date which is ...
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Compositional Modeling of Two-Phase Flow in Porous Media Using Semi-Implicit Scheme
... The paper is structured as follows. In Section II, the mathematical model is formulated by means of partial differ- ential equations representing the conservation laws, Darcy’s laws, and by means of the conditions of ...
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Numerical convergence of the random vortex method for complex flows
... the moment, no complete theory has been developped to express this condition. Anyway, once the stability conditions are satised (which depends primarily on a convenient choice of discretization parameters compared ...
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Discrete classification technique applied to TV advertisements liking recognition system based on low-cost EEG headsets
... Finally, a new approach based on discretization algorithm is presented in this section. In this case, the input values will be classified throughout continuous techniques. The new algorithm, based on Ameva, will ...
22
On the Forward and Inverse Computational Wave Propagation Problems.
... various methods such as steady-state Rayleigh method [89], multi-offset phase analysis [90], extended spatial autocorrelation [91], high-resolution linear Radon transform [92], transform methods such as ...
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