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  • Open Access

    ARTICLE

    Deep Neural Network Architecture Search via Decomposition-Based Multi-Objective Stochastic Fractal Search

    Hongshang Xu1, Bei Dong1,2,*, Xiaochang Liu1, Xiaojun Wu1,2

    Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 185-202, 2023, DOI:10.32604/iasc.2023.041177

    Abstract Deep neural networks often outperform classical machine learning algorithms in solving real-world problems. However, designing better networks usually requires domain expertise and consumes significant time and computing resources. Moreover, when the task changes, the original network architecture becomes outdated and requires redesigning. Thus, Neural Architecture Search (NAS) has gained attention as an effective approach to automatically generate optimal network architectures. Most NAS methods mainly focus on achieving high performance while ignoring architectural complexity. A myriad of research has revealed that network performance and structural complexity are often positively correlated. Nevertheless, complex network structures will bring enormous computing resources. To cope… More >

  • Open Access

    ARTICLE

    A Novel Fractional Dengue Transmission Model in the Presence of Wolbachia Using Stochastic Based Artificial Neural Network

    Zeshan Faiz1, Iftikhar Ahmed1, Dumitru Baleanu2,3,4, Shumaila Javeed1,5,6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1217-1238, 2024, DOI:10.32604/cmes.2023.029879

    Abstract The purpose of this research work is to investigate the numerical solutions of the fractional dengue transmission model (FDTM) in the presence of Wolbachia using the stochastic-based Levenberg-Marquardt neural network (LM-NN) technique. The fractional dengue transmission model (FDTM) consists of 12 compartments. The human population is divided into four compartments; susceptible humans (Sh), exposed humans (Eh), infectious humans (Ih), and recovered humans (Rh). Wolbachia-infected and Wolbachia-uninfected mosquito population is also divided into four compartments: aquatic (eggs, larvae, pupae), susceptible, exposed, and infectious. We investigated three different cases of vertical transmission probability (η), namely when Wolbachia-free mosquitoes persist only (η =… 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

    ARTICLE

    RB-DEM Modeling and Simulation of Non-Persisting Rough Open Joints Based on the IFS-Enhanced Method

    Hangtian Song1,2, Xudong Chen1,2, Chun Zhu3, Qian Yin4, Wei Wang1,2, Qingxiang Meng1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 337-359, 2024, DOI:10.32604/cmes.2023.031496

    Abstract When the geological environment of rock masses is disturbed, numerous non-persisting open joints can appear within it. It is crucial to investigate the effect of open joints on the mechanical properties of rock mass. However, it has been challenging to generate realistic open joints in traditional experimental tests and numerical simulations. This paper presents a novel solution to solve the problem. By utilizing the stochastic distribution of joints and an enhanced-fractal interpolation system (IFS) method, rough curves with any orientation can be generated. The Douglas-Peucker algorithm is then applied to simplify these curves by removing unnecessary points while preserving their… More > Graphic Abstract

    RB-DEM Modeling and Simulation of Non-Persisting Rough Open Joints Based on the IFS-Enhanced Method

  • Open Access

    ARTICLE

    Analytical and Numerical Methods to Study the MFPT and SR of a Stochastic Tumor-Immune Model

    Ying Zhang1, Wei Li1,*, Guidong Yang1, Snezana Kirin2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2177-2199, 2024, DOI:10.32604/cmes.2023.030728

    Abstract The Mean First-Passage Time (MFPT) and Stochastic Resonance (SR) of a stochastic tumor-immune model with noise perturbation are discussed in this paper. Firstly, considering environmental perturbation, Gaussian white noise and Gaussian colored noise are introduced into a tumor growth model under immune surveillance. As follows, the long-time evolution of the tumor characterized by the Stationary Probability Density (SPD) and MFPT is obtained in theory on the basis of the Approximated Fokker-Planck Equation (AFPE). Herein the recurrence of the tumor from the extinction state to the tumor-present state is more concerned in this paper. A more efficient algorithm of Back-Propagation Neural… More >

  • Open Access

    ARTICLE

    A Stochastic Model to Assess the Epidemiological Impact of Vaccine Booster Doses on COVID-19 and Viral Hepatitis B Co-Dynamics with Real Data

    Andrew Omame1,2,*, Mujahid Abbas3,6, Dumitru Baleanu4,5,6

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2973-3012, 2024, DOI:10.32604/cmes.2023.029681

    Abstract A patient co-infected with COVID-19 and viral hepatitis B can be at more risk of severe complications than the one infected with a single infection. This study develops a comprehensive stochastic model to assess the epidemiological impact of vaccine booster doses on the co-dynamics of viral hepatitis B and COVID-19. The model is fitted to real COVID-19 data from Pakistan. The proposed model incorporates logistic growth and saturated incidence functions. Rigorous analyses using the tools of stochastic calculus, are performed to study appropriate conditions for the existence of unique global solutions, stationary distribution in the sense of ergodicity and disease… More >

  • Open Access

    ARTICLE

    Chimp Optimization Algorithm Based Feature Selection with Machine Learning for Medical Data Classification

    Firas Abedi1, Hayder M. A. Ghanimi2, Abeer D. Algarni3, Naglaa F. Soliman3,*, Walid El-Shafai4,5, Ali Hashim Abbas6, Zahraa H. Kareem7, Hussein Muhi Hariz8, Ahmed Alkhayyat9

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2791-2814, 2023, DOI:10.32604/csse.2023.038762

    Abstract Data mining plays a crucial role in extracting meaningful knowledge from large-scale data repositories, such as data warehouses and databases. Association rule mining, a fundamental process in data mining, involves discovering correlations, patterns, and causal structures within datasets. In the healthcare domain, association rules offer valuable opportunities for building knowledge bases, enabling intelligent diagnoses, and extracting invaluable information rapidly. This paper presents a novel approach called the Machine Learning based Association Rule Mining and Classification for Healthcare Data Management System (MLARMC-HDMS). The MLARMC-HDMS technique integrates classification and association rule mining (ARM) processes. Initially, the chimp optimization algorithm-based feature selection (COAFS)… More >

  • Open Access

    ARTICLE

    Stochastic Models to Mitigate Sparse Sensor Attacks in Continuous-Time Non-Linear Cyber-Physical Systems

    Borja Bordel Sánchez1,*, Ramón Alcarria2, Tomás Robles1

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3189-3218, 2023, DOI:10.32604/cmc.2023.039466

    Abstract Cyber-Physical Systems are very vulnerable to sparse sensor attacks. But current protection mechanisms employ linear and deterministic models which cannot detect attacks precisely. Therefore, in this paper, we propose a new non-linear generalized model to describe Cyber-Physical Systems. This model includes unknown multivariable discrete and continuous-time functions and different multiplicative noises to represent the evolution of physical processes and random effects in the physical and computational worlds. Besides, the digitalization stage in hardware devices is represented too. Attackers and most critical sparse sensor attacks are described through a stochastic process. The reconstruction and protection mechanisms are based on a weighted… More >

  • Open Access

    ARTICLE

    An Interpolation Method for Karhunen–Loève Expansion of Random Field Discretization

    Zi Han1,*, Zhentian Huang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 245-272, 2024, DOI:10.32604/cmes.2023.029708

    Abstract In the context of global mean square error concerning the number of random variables in the representation, the Karhunen–Loève (KL) expansion is the optimal series expansion method for random field discretization. The computational efficiency and accuracy of the KL expansion are contingent upon the accurate resolution of the Fredholm integral eigenvalue problem (IEVP). The paper proposes an interpolation method based on different interpolation basis functions such as moving least squares (MLS), least squares (LS), and finite element method (FEM) to solve the IEVP. Compared with the Galerkin method based on finite element or Legendre polynomials, the main advantage of the… More > Graphic Abstract

    An Interpolation Method for Karhunen–Loève Expansion of Random Field Discretization

  • Open Access

    ARTICLE

    Outage Probability Analysis for D2D-Enabled Heterogeneous Cellular Networks with Exclusion Zone: A Stochastic Geometry Approach

    Yulei Wang1, Li Feng1,*, Shumin Yao1,2, Hong Liang1, Haoxu Shi1, Yuqiang Chen3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 639-661, 2024, DOI:10.32604/cmes.2023.029565

    Abstract Interference management is one of the most important issues in the device-to-device (D2D)-enabled heterogeneous cellular networks (HetCNets) due to the coexistence of massive cellular and D2D devices in which D2D devices reuse the cellular spectrum. To alleviate the interference, an efficient interference management way is to set exclusion zones around the cellular receivers. In this paper, we adopt a stochastic geometry approach to analyze the outage probabilities of cellular and D2D users in the D2D-enabled HetCNets. The main difficulties contain three aspects: 1) how to model the location randomness of base stations, cellular and D2D users in practical networks; 2)… More >

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