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  • Open Access

    ARTICLE

    On the Application of Mixed Models of Probability and Convex Set for Time-Variant Reliability Analysis

    Fangyi Li*, Dachang Zhu*, Huimin Shi

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1981-1999, 2024, DOI:10.32604/cmes.2023.031332

    Abstract In time-variant reliability problems, there are a lot of uncertain variables from different sources. Therefore, it is important to consider these uncertainties in engineering. In addition, time-variant reliability problems typically involve a complex multilevel nested optimization problem, which can result in an enormous amount of computation. To this end, this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model. In this method, the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a time-independent reliability problem. Further, to solve the… More >

  • Open Access

    ARTICLE

    Distributed Stochastic Optimization with Compression for Non-Strongly Convex Objectives

    Xuanjie Li, Yuedong Xu*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 459-481, 2024, DOI:10.32604/cmes.2023.043247

    Abstract We are investigating the distributed optimization problem, where a network of nodes works together to minimize a global objective that is a finite sum of their stored local functions. Since nodes exchange optimization parameters through the wireless network, large-scale training models can create communication bottlenecks, resulting in slower training times. To address this issue, CHOCO-SGD was proposed, which allows compressing information with arbitrary precision without reducing the convergence rate for strongly convex objective functions. Nevertheless, most convex functions are not strongly convex (such as logistic regression or Lasso), which raises the question of whether this algorithm can be applied to… More >

  • 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

    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 to the large-scale equation solution,… More >

  • Open Access

    ARTICLE

    Binary Tomography Reconstruction with Limited-Data by a Convex Level-Set Method

    Haytham A. Ali1,2,*, Hiroyuki Kudo1

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3741-3756, 2022, DOI:10.32604/cmc.2022.029394

    Abstract This paper proposes a new level-set-based shape recovery approach that can be applied to a wide range of binary tomography reconstructions. In this technique, we derive generic evolution equations for shape reconstruction in terms of the underlying level-set parameters. We show that using the appropriate basis function to parameterize the level-set function results in an optimization problem with a small number of parameters, which overcomes many of the problems associated with the traditional level-set approach. More concretely, in this paper, we use Gaussian functions as a basis function placed at sparse grid points to represent the parametric level-set function and… More >

  • Open Access

    ARTICLE

    Optimal Beamforming for Secure Transmit in Practical Wireless Networks

    Qiuqin Yang1, Linfang Li1, Ming-Xing Luo1,*, Xiaojun Wang2

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1863-1877, 2022, DOI:10.32604/cmc.2022.027120

    Abstract In real communication systems, secure and low-energy transmit scheme is very important. So far, most of schemes focus on secure transmit in special scenarios. In this paper, our goal is to propose a secure protocol in wireless networks involved various factors including artificial noise (AN), the imperfect receiver and imperfect channel state information (CSI) of eavesdropper, weight of beamforming (BF) vector, cooperative jammers (CJ), multiple receivers, and multiple eavesdroppers, and the analysis shows that the protocol can reduce the transmission power, and at the same time the safe reachability rate is greater than our pre-defined value, and the analysis results… More >

  • Open Access

    ARTICLE

    Resource Allocation for Throughput Maximization in Cognitive Radio Network with NOMA

    Xiaoli He1, Yu Song2,3,*, Yu Xue4, Muhammad Owais5, Weijian Yang1, Xinwen Cheng1

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 195-212, 2022, DOI:10.32604/cmc.2022.017105

    Abstract Spectrum resources are the precious and limited natural resources. In order to improve the utilization of spectrum resources and maximize the network throughput, this paper studies the resource allocation of the downlink cognitive radio network with non-orthogonal multiple access (CRN-NOMA). NOMA, as the key technology of the fifth-generation communication (5G), can effectively increase the capacity of 5G networks. The optimization problem proposed in this paper aims to maximize the number of secondary users (SUs) accessing the system and the total throughput in the CRN-NOMA. Under the constraints of total power, minimum rate, interference and SINR, CRN-NOMA throughput is maximized by… More >

  • Open Access

    ARTICLE

    Saddle Point Optimality Criteria of Interval Valued Non-Linear Programming Problem

    Md Sadikur Rahman1, Emad E. Mahmoud2, Ali Akbar Shaikh1,*, Abdel-Haleem Abdel-Aty3,4, Asoke Kumar Bhunia1

    Computer Systems Science and Engineering, Vol.38, No.3, pp. 351-364, 2021, DOI:10.32604/csse.2021.015451

    Abstract The present paper aims to develop the Kuhn-Tucker and Fritz John criteria for saddle point optimality of interval-valued nonlinear programming problem. To achieve the study objective, we have proposed the definition of minimizer and maximizer of an interval-valued non-linear programming problem. Also, we have introduced the interval-valued Fritz-John and Kuhn Tucker saddle point problems. After that, we have established both the necessary and sufficient optimality conditions of an interval-valued non-linear minimization problem. Next, we have shown that both the saddle point conditions (Fritz-John and Kuhn-Tucker) are sufficient without any convexity requirements. Then with the convexity requirements, we have established that… More >

  • Open Access

    ARTICLE

    Improving POI Recommendation via Non-Convex Regularized Tensor Completion

    Ming Zhao*, Tao Liu

    Journal of Information Hiding and Privacy Protection, Vol.2, No.3, pp. 125-134, 2020, DOI:10.32604/jihpp.2020.010211

    Abstract The problem of low accuracy of POI (Points of Interest) recommendation in LBSN (Location-Based Social Networks) has not been effectively solved. In this paper, a POI recommendation algorithm based on nonconvex regularized tensor completion is proposed. The fourth-order tensor is constructed by using the current location category, the next location category, time and season, the regularizer is added to the objective function of tensor completion to prevent over-fitting and reduce the error of the model. The proximal algorithm is used to solve the objective function, and the adaptive momentum is introduced to improve the efficiency of the solution. The experimental… More >

  • Open Access

    ARTICLE

    A Bayesian Updating Method for Non-Probabilistic Reliability Assessment of Structures with Performance Test Data

    Jiaqi He1, Yangjun Luo1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 777-800, 2020, DOI:10.32604/cmes.2020.010688

    Abstract For structures that only the predicted bounds of uncertainties are available, this study proposes a Bayesian method to logically evaluate the nonprobabilistic reliability of structures based on multi-ellipsoid convex model and performance test data. According to the given interval ranges of uncertainties, we determine the initial characteristic parameters of a multi-ellipsoid convex set. Moreover, to update the plausibility of characteristic parameters, a Bayesian network for the information fusion of prior uncertainty knowledge and subsequent performance test data is constructed. Then, an updated multi-ellipsoid set with the maximum likelihood of the performance test data can be achieved. The credible non-probabilistic reliability… More >

  • Open Access

    ARTICLE

    Improving Initial Flattening of Convex-Shaped Free-Form Mesh Surface Patches Using a Dynamic Virtual Boundary

    Erdem Yavuz1,∗, Rıfat Yazıcı2, Mustafa Cem Kasapba¸sı2, Turgay Tugay Bilgin1

    Computer Systems Science and Engineering, Vol.34, No.6, pp. 339-355, 2019, DOI:10.32604/csse.2019.34.339

    Abstract This study proposes an efficient algorithm for improving flattening result of triangular mesh surface patches having a convex shape. The proposed approach, based on barycentric mapping technique, incorporates a dynamic virtual boundary, which considerably improves initial mapping result. The dynamic virtual boundary approach is utilized to reduce the distortions for the triangles near the boundary caused by the nature of convex combination technique. Mapping results of the proposed algorithm and the base technique are compared by area and shape accuracy metrics measured for several sample surfaces. The results prove the success of the proposed approach with respect to the base… More >

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