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  • Open Access

    REVIEW

    An Overview of Sequential Approximation in Topology Optimization of Continuum Structure

    Kai Long1, Ayesha Saeed1, Jinhua Zhang2, Yara Diaeldin1, Feiyu Lu1, Tao Tao3, Yuhua Li1,*, Pengwen Sun4, Jinshun Yan5

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 43-67, 2024, DOI:10.32604/cmes.2023.031538 - 30 December 2023

    Abstract This paper offers an extensive overview of the utilization of sequential approximate optimization approaches in the context of numerically simulated large-scale continuum structures. These structures, commonly encountered in engineering applications, often involve complex objective and constraint functions that cannot be readily expressed as explicit functions of the design variables. As a result, sequential approximation techniques have emerged as the preferred strategy for addressing a wide array of topology optimization challenges. Over the past several decades, topology optimization methods have been advanced remarkably and successfully applied to solve engineering problems incorporating diverse physical backgrounds. In comparison… More >

  • Open Access

    ARTICLE

    Bifurcation Analysis of a Nonlinear Vibro-Impact System with an Uncertain Parameter via OPA Method

    Dongmei Huang1, Dang Hong2, Wei Li1,*, Guidong Yang1, Vesna Rajic3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 509-524, 2024, DOI:10.32604/cmes.2023.029215 - 22 September 2023

    Abstract In this paper, the bifurcation properties of the vibro-impact systems with an uncertain parameter under the impulse and harmonic excitations are investigated. Firstly, by means of the orthogonal polynomial approximation (OPA) method, the nonlinear damping and stiffness are expanded into the linear combination of the state variable. The condition for the appearance of the vibro-impact phenomenon is to be transformed based on the calculation of the mean value. Afterwards, the stochastic vibro-impact system can be turned into an equivalent high-dimensional deterministic non-smooth system. Two different Poincaré sections are chosen to analyze the bifurcation properties and… More >

  • Open Access

    ARTICLE

    Fusing Supervised and Unsupervised Measures for Attribute Reduction

    Tianshun Xing, Jianjun Chen*, Taihua Xu, Yan Fan

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 561-581, 2023, DOI:10.32604/iasc.2023.037874 - 29 April 2023

    Abstract It is well-known that attribute reduction is a crucial action of rough set. The significant characteristic of attribute reduction is that it can reduce the dimensions of data with clear semantic explanations. Normally, the learning performance of attributes in derived reduct is much more crucial. Since related measures of rough set dominate the whole process of identifying qualified attributes and deriving reduct, those measures may have a direct impact on the performance of selected attributes in reduct. However, most previous researches about attribute reduction take measures related to either supervised perspective or unsupervised perspective, which… More >

  • Open Access

    ARTICLE

    Real-Time Multi-Feature Approximation Model-Based Efficient Brain Tumor Classification Using Deep Learning Convolution Neural Network Model

    Amarendra Reddy Panyala1,2, M. Baskar3,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3883-3899, 2023, DOI:10.32604/csse.2023.037050 - 03 April 2023

    Abstract The deep learning models are identified as having a significant impact on various problems. The same can be adapted to the problem of brain tumor classification. However, several deep learning models are presented earlier, but they need better classification accuracy. An efficient Multi-Feature Approximation Based Convolution Neural Network (CNN) model (MFA-CNN) is proposed to handle this issue. The method reads the input 3D Magnetic Resonance Imaging (MRI) images and applies Gabor filters at multiple levels. The noise-removed image has been equalized for its quality by using histogram equalization. Further, the features like white mass, grey… More >

  • Open Access

    ARTICLE

    Improved QoS-Secure Routing in MANET Using Real-Time Regional ME Feature Approximation

    Y. M. Mahaboob John1,*, G. Ravi2

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3653-3666, 2023, DOI:10.32604/csse.2023.036916 - 03 April 2023

    Abstract Mobile Ad-hoc Network (MANET) routing problems are thoroughly studied several approaches are identified in support of MANET. Improve the Quality of Service (QoS) performance of MANET is achieving higher performance. To reduce this drawback, this paper proposes a new secure routing algorithm based on real-time partial ME (Mobility, energy) approximation. The routing method RRME (Real-time Regional Mobility Energy) divides the whole network into several parts, and each node’s various characteristics like mobility and energy are randomly selected neighbors accordingly. It is done in the path discovery phase, estimated to identify and remove malicious nodes. In… More >

  • Open Access

    ARTICLE

    Approximations by Ideal Minimal Structure with Chemical Application

    Rodyna A. Hosny1, Radwan Abu-Gdairi2, Mostafa K. El-Bably3,*

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3073-3085, 2023, DOI:10.32604/iasc.2023.034234 - 15 March 2023

    Abstract The theory of rough set represents a non-statistical methodology for analyzing ambiguity and imprecise information. It can be characterized by two crisp sets, named the upper and lower approximations that are used to determine the boundary region and accurate measure of any subset. This article endeavors to achieve the best approximation and the highest accuracy degree by using the minimal structure approximation space via ideal . The novel approach (indicated by ) modifies the approximation space to diminish the boundary region and enhance the measure of accuracy. The suggested method is more accurate than Pawlak’s More >

  • Open Access

    ARTICLE

    A Numerical Investigation Based on Exponential Collocation Method for Nonlinear SITR Model of COVID-19

    Mohammad Aslefallah1, Şuayip Yüzbaşi2, Saeid Abbasbandy1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1687-1706, 2023, DOI:10.32604/cmes.2023.025647 - 06 February 2023

    Abstract In this work, the exponential approximation is used for the numerical simulation of a nonlinear SITR model as a system of differential equations that shows the dynamics of the new coronavirus (COVID-19). The SITR mathematical model is divided into four classes using fractal parameters for COVID-19 dynamics, namely, susceptible (S), infected (I), treatment (T), and recovered (R). The main idea of the presented method is based on the matrix representations of the exponential functions and their derivatives using collocation points. To indicate the usefulness of this method, we employ it in some cases. For error More > Graphic Abstract

    A Numerical Investigation Based on Exponential Collocation Method for Nonlinear SITR Model of COVID-19

  • Open Access

    ARTICLE

    Computing of LQR Technique for Nonlinear System Using Local Approximation

    Aamir Shahzad1, Ali Altalbe2,*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 853-871, 2023, DOI:10.32604/csse.2023.035575 - 20 January 2023

    Abstract The main idea behind the present research is to design a state-feedback controller for an underactuated nonlinear rotary inverted pendulum module by employing the linear quadratic regulator (LQR) technique using local approximation. The LQR is an excellent method for developing a controller for nonlinear systems. It provides optimal feedback to make the closed-loop system robust and stable, rejecting external disturbances. Model-based optimal controller for a nonlinear system such as a rotatory inverted pendulum has not been designed and implemented using Newton-Euler, Lagrange method, and local approximation. Therefore, implementing LQR to an underactuated nonlinear system was… More >

  • Open Access

    ARTICLE

    RMCARTAM For DDoS Attack Mitigation in SDN Using Machine Learning

    M. Revathi, V. V. Ramalingam*, B. Amutha

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 3023-3036, 2023, DOI:10.32604/csse.2023.033600 - 21 December 2022

    Abstract The impact of a Distributed Denial of Service (DDoS) attack on Software Defined Networks (SDN) is briefly analyzed. Many approaches to detecting DDoS attacks exist, varying on the feature being considered and the method used. Still, the methods have a deficiency in the performance of detecting DDoS attacks and mitigating them. To improve the performance of SDN, an efficient Real-time Multi-Constrained Adaptive Replication and Traffic Approximation Model (RMCARTAM) is sketched in this article. The RMCARTAM considers different parameters or constraints in running different controllers responsible for handling incoming packets. The model is designed with multiple… More >

  • Open Access

    ARTICLE

    On the Approximation of Fractal-Fractional Differential Equations Using Numerical Inverse Laplace Transform Methods

    Kamran1, Siraj Ahmad1, Kamal Shah2,3,*, Thabet Abdeljawad2,4,*, Bahaaeldin Abdalla2

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2743-2765, 2023, DOI:10.32604/cmes.2023.023705 - 23 November 2022

    Abstract Laplace transform is one of the powerful tools for solving differential equations in engineering and other science subjects. Using the Laplace transform for solving differential equations, however, sometimes leads to solutions in the Laplace domain that are not readily invertible to the real domain by analytical means. Thus, we need numerical inversion methods to convert the obtained solution from Laplace domain to a real domain. In this paper, we propose a numerical scheme based on Laplace transform and numerical inverse Laplace transform for the approximate solution of fractal-fractional differential equations with order . Our proposed… More > Graphic Abstract

    On the Approximation of Fractal-Fractional Differential Equations Using Numerical Inverse Laplace Transform Methods

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