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  • Open Access


    An Efficient Meshless Method for Hyperbolic Telegraph Equations in (1 + 1) Dimensions

    Fuzhang Wang1,2, Enran Hou2,*, Imtiaz Ahmad3, Hijaz Ahmad4, Yan Gu5

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 687-698, 2021, DOI:10.32604/cmes.2021.014739

    Abstract Numerical solutions of the second-order one-dimensional hyperbolic telegraph equations are presented using the radial basis functions. The purpose of this paper is to propose a simple novel direct meshless scheme for solving hyperbolic telegraph equations. This is fulfilled by considering time variable as normal space variable. Under this scheme, there is no need to remove time-dependent variable during the whole solution process. Since the numerical solution accuracy depends on the condition of coefficient matrix derived from the radial basis function method. We propose a simple shifted domain method, which can avoid the full-coefficient interpolation matrix More >

  • Open Access


    Comparison of Detection and Classification of Hard Exudates Using Artificial Neural System vs. SVM Radial Basis Function in Diabetic Retinopathy

    V. Sudha1,*, T. R. Ganesh Babu2, N. Vikram1, R. Raja2

    Molecular & Cellular Biomechanics, Vol.18, No.3, pp. 139-145, 2021, DOI:10.32604/mcb.2021.016056

    Abstract Diabetic Retinopathy (DR) is a disease that occurs in the eye which results in blindness as it passes to proliferative stage. Diabetes can significantly result in symptoms like blurring of vision, kidney failure, nervous damage. Hence it has become necessary to identify retinal damage that occurs in diabetic eye due to raised glucose level in its initial stage itself. Hence automated detection of anamoly has become very essential. The appearance of crimson and yellow lesions is considered as the earliest symptoms of DR which are called as hemorrhages and exudates. If DR is analysed at… More >

  • Open Access


    Prediction of Parkinson’s Disease Using Improved Radial Basis Function Neural Network

    Rajalakshmi Shenbaga Moorthy1,*, P. Pabitha2

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3101-3119, 2021, DOI:10.32604/cmc.2021.016489

    Abstract Parkinson’s disease is a neurogenerative disorder and it is difficult to diagnose as no therapies may slow down its progression. This paper contributes a novel analytic system for Parkinson’s Disease Prediction mechanism using Improved Radial Basis Function Neural Network (IRBFNN). Particle swarm optimization (PSO) with K-means is used to find the hidden neuron’s centers to improve the accuracy of IRBFNN. The performance of RBFNN is seriously affected by the centers of hidden neurons. Conventionally K-means was used to find the centers of hidden neurons. The problem of sensitiveness to the random initial centroid in K-means… More >

  • Open Access


    Hybrid Metamodeling/Metaheuristic Assisted Multi-Transmitters Placement Planning

    Amir Parnianifard1, Muhammad Saadi2, Manus Pengnoo1, Muhammad Ali Imran3, Sattam Al Otaibi4, Pruk Sasithong1, Pisit Vanichchanunt5, Tuchsanai Polysuwan6, Lunchakorn Wuttisittikulkij1,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 569-587, 2021, DOI:10.32604/cmc.2021.015730

    Abstract With every passing day, the demand for data traffic is increasing, and this urges the research community not only to look for an alternating spectrum for communication but also urges radio frequency planners to use the existing spectrum efficiently. Cell sizes are shrinking with every upcoming communication generation, which makes base station placement planning even more complex and cumbersome. In order to make the next-generation cost-effective, it is important to design a network in such a way that it utilizes the minimum number of base stations while ensuring seamless coverage and quality of service. This… More >

  • Open Access


    Study on the Improvement of the Application of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise in Hydrology Based on RBFNN Data Extension Technology

    Jinping Zhang1,2, Youlai Jin1, Bin Sun1,*, Yuping Han3, Yang Hong4

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.2, pp. 755-770, 2021, DOI:10.32604/cmes.2021.012686

    Abstract The complex nonlinear and non-stationary features exhibited in hydrologic sequences make hydrological analysis and forecasting difficult. Currently, some hydrologists employ the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method, a new time-frequency analysis method based on the empirical mode decomposition (EMD) algorithm, to decompose non-stationary raw data in order to obtain relatively stationary components for further study. However, the endpoint effect in CEEMDAN is often neglected, which can lead to decomposition errors that reduce the accuracy of the research results. In this study, we processed an original runoff sequence using the radial basis… More >

  • Open Access


    Multiquadric Radial Basis Function Approximation Scheme for Solution of Total Variation Based Multiplicative Noise Removal Model

    Mushtaq Ahmad Khan1,*, Ahmed B. Altamimi2, Zawar Hussain Khan3, Khurram Shehzad Khattak3, Sahib Khan4,*, Asmat Ullah3, Murtaza Ali1

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.1, pp. 55-88, 2021, DOI:10.32604/cmes.2021.011163

    Abstract This article introduces a fast meshless algorithm for the numerical solution nonlinear partial differential equations (PDE) by Radial Basis Functions (RBFs) approximation connected with the Total Variation (TV)-based minimization functional and to show its application to image denoising containing multiplicative noise. These capabilities used within the proposed algorithm have not only the quality of image denoising, edge preservation but also the property of minimization of staircase effect which results in blocky effects in the images. It is worth mentioning that the recommended method can be easily employed for nonlinear problems due to the lack of More >

  • Open Access


    Application of Radial Basis Function Networks with Feature Selection for GDP Per Capita Estimation Based on Academic Parameters

    Abdullah Erdal Tümer1,∗, Aytekin Akku¸s2

    Computer Systems Science and Engineering, Vol.34, No.3, pp. 145-150, 2019, DOI:10.32604/csse.2019.34.145

    Abstract In this work, a system based on Radial Basis Function Network was developed to estimate Gross Domestic Product per capita. The data set based on 180 academic parameters of 13 Organisation for Economic Co-operation and Development countries was used to verify the effectiveness and accuracy of the proposed method. Gross Domestic Product per capita was studied to be estimated for the first time with academic parameters in this study. The system has been optimized using feature selection method to eliminate unimportant features. Radial Basis Function network results and Radial Basis Function network with feature selection More >

  • Open Access


    Real-Time Thermomechanical Modeling of PV Cell Fabrication via a POD-Trained RBF Interpolation Network

    Arka Das1, Anthony Khoury1, Eduardo Divo1, *, Victor Huayamave1, Andres Ceballos2, Ron Eaglin2, Alain Kassab3, Adam Payne4, Vijay Yelundur4, Hubert Seigneur5

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.3, pp. 757-777, 2020, DOI:10.32604/cmes.2020.08164

    Abstract This paper presents a numerical reduced order model framework to simulate the physics of the thermomechanical processes that occur during c-Si photovoltaic (PV) cell fabrication. A response surface based on a radial basis function (RBF) interpolation network trained by a Proper Orthogonal Decomposition (POD) of the solution fields is developed for fast and accurate approximations of thermal loading conditions on PV cells during the fabrication processes. The outcome is a stand-alone computational tool that provides, in real time, the quantitative and qualitative thermomechanical response as a function of user-controlled input parameters for fabrication processes with More >

  • Open Access


    Meshless Method with Enriched Radial Basis Functions for Fracture Mechanics

    P.H. Wen1, M.H. Aliabadi2

    Structural Durability & Health Monitoring, Vol.3, No.2, pp. 107-120, 2007, DOI:10.3970/sdhm.2007.003.107

    Abstract In the last decade, meshless methods for solving differential equations have become a promising alternative to the finite element and boundary element methods. Based on the variation of potential energy, the element-free Galerkin method is developed on the basis of finite element method by the use of radial basis function interpolation. An enriched radial basis function is formulated to capture the stress singularity at the crack tip. The usual advantages of finite element method are retained in this method but now significant improvement of accuracy. Neither the connectivity of mesh in the domain by the More >

  • Open Access


    2D and 3D Multiphysics Voronoi Cells, Based on Radial Basis Functions, for Direct Mesoscale Numerical Simulation (DMNS) of the Switching Phenomena in Ferroelectric Polycrystalline Materials

    Peter L. Bishay1, Satya N. Atluri1

    CMC-Computers, Materials & Continua, Vol.33, No.1, pp. 19-62, 2013, DOI:10.3970/cmc.2013.033.019

    Abstract In this paper, 2D and 3D Multiphysics Voronoi Cells (MVCs) are developed, for the Direct Mesoscale Numerical Simulation (DMNS) of the switching phenomena in ferroelectric polycrystalline materials. These arbitrarily shaped MVCs (arbitrary polygons in 2D, and arbitrary polyhedrons in 3D with each face being an arbitrary polygon) are developed, based on assuming radial basis functions to represent the internal primal variables (mechanical displacements and electric potential), and assuming linear functions to represent the primal variables on the element boundaries. For the 3D case, the linear functions used to represent the primal variables on each of… More >

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