The time fractional order differential equations are fundamental tools that are used for modeling neuronal dynamics. These equations are obtained by substituting the time derivative of order  where , in the standard equation with the Caputo fractional formula. In this paper, two implicit difference schemes: the linearly Euler implicit and the Crank-Nicolson (CN) finite difference schemes, are employed in solving a one-dimensional time-fractional semilinear equation with Dirichlet boundary conditions. Moreover, the consistency, stability and convergence of the proposed schemes are investigated. We prove that the IEM is unconditionally stable, while CNM is conditionally stable. Furthermore, a comparative study between these two s

Many fuzzy clustering are based on within-cluster scatter with a compactness measure , but in this paper explaining new fuzzy clustering method which depend on within-cluster scatter with a compactness measure and between-cluster scatter with a separation measure called the fuzzy compactness and separation (FCS). The fuzzy linear discriminant analysis (FLDA) based on within-cluster scatter matrix and between-cluster scatter matrix . Then two fuzzy scattering matrices in the objective function assure the compactness between data elements and cluster centers .To test the optimal number of clusters using validation clustering method is discuss .After that an illustrate example are applied.

    In this research, aflatoxins were produced, extracted, isolated, and purified in order to optimize the storage conditions of feed. Using a preparative thin layer chromatography (TLC) method, with commercially available plates of 1.5 to 2.0 mm, B1 aflatoxin was isolated from the feed samples of whole wheat, maize, and crushed rice, and the procedure was repeated four times. A purity value of 99 % for B1 aflatoxin was achieved and tested using spectrophotometric and chromatographic methods. As solvents, acetone:water (85:15l) was used for aflatoxin extraction from the feed sample, whereas methanol: water (50: 50) was used for trichothecenes extraction. The primary findings of this research indicate that B1 aflatoxin reac

Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

    This paper  concerns with the state and proof the existence and uniqueness theorem of triple state vector solution (TSVS) for the triple nonlinear parabolic partial differential equations (TNPPDEs) ,and triple state vector equations (TSVEs), under suitable assumptions. when the continuous classical triple control vector (CCTCV) is given by using the method of Galerkin (MGA). The existence theorem of a continuous classical optimal triple control vector (CCTOCV) for the continuous classical optimal control governing by the TNPPDEs under suitable conditions is proved.  

In this paper Hermite interpolation method is used for solving linear and non-linear second order singular multi point boundary value problems with nonlocal condition. The approximate solution is found in the form of a rapidly convergent polynomial. We discuss behavior of the solution in the neighborhood of the singularity point which appears to perform satisfactorily for singular problems. The examples to demonstrate the applicability and efficiency of the method have been given.