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  • Open Access

    ARTICLE

    Numerical Exploration of Asymmetrical Impact Dynamics: Unveiling Nonlinearities in Collision Problems and Resilience of Reinforced Concrete Structures

    AL-Bukhaiti Khalil1, Yanhui Liu1,*, Shichun Zhao1, Daguang Han2

    Structural Durability & Health Monitoring, Vol.18, No.3, pp. 223-254, 2024, DOI:10.32604/sdhm.2024.044751

    Abstract This study provides a comprehensive analysis of collision and impact problems’ numerical solutions, focusing on geometric, contact, and material nonlinearities, all essential in solving large deformation problems during a collision. The initial discussion revolves around the stress and strain of large deformation during a collision, followed by explanations of the fundamental finite element solution method for addressing such issues. The hourglass mode’s control methods, such as single-point reduced integration and contact-collision algorithms are detailed and implemented within the finite element framework. The paper further investigates the dynamic response and failure modes of Reinforced Concrete (RC)… More >

  • Open Access

    ARTICLE

    Appropriate Combination of Crossover Operator and Mutation Operator in Genetic Algorithms for the Travelling Salesman Problem

    Zakir Hussain Ahmed1,*, Habibollah Haron2, Abdullah Al-Tameem3

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2399-2425, 2024, DOI:10.32604/cmc.2024.049704

    Abstract Genetic algorithms (GAs) are very good metaheuristic algorithms that are suitable for solving NP-hard combinatorial optimization problems. A simple GA begins with a set of solutions represented by a population of chromosomes and then uses the idea of survival of the fittest in the selection process to select some fitter chromosomes. It uses a crossover operator to create better offspring chromosomes and thus, converges the population. Also, it uses a mutation operator to explore the unexplored areas by the crossover operator, and thus, diversifies the GA search space. A combination of crossover and mutation operators… More >

  • Open Access

    ARTICLE

    A Cooperated Imperialist Competitive Algorithm for Unrelated Parallel Batch Machine Scheduling Problem

    Deming Lei*, Heen Li

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1855-1874, 2024, DOI:10.32604/cmc.2024.049480

    Abstract This study focuses on the scheduling problem of unrelated parallel batch processing machines (BPM) with release times, a scenario derived from the moulding process in a foundry. In this process, a batch is initially formed, placed in a sandbox, and then the sandbox is positioned on a BPM for moulding. The complexity of the scheduling problem increases due to the consideration of BPM capacity and sandbox volume. To minimize the makespan, a new cooperated imperialist competitive algorithm (CICA) is introduced. In CICA, the number of empires is not a parameter, and four empires are maintained More >

  • Open Access

    ARTICLE

    Real-Time Prediction of Urban Traffic Problems Based on Artificial Intelligence-Enhanced Mobile Ad Hoc Networks (MANETS)

    Ahmed Alhussen1, Arshiya S. Ansari2,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1903-1923, 2024, DOI:10.32604/cmc.2024.049260

    Abstract Traffic in today’s cities is a serious problem that increases travel times, negatively affects the environment, and drains financial resources. This study presents an Artificial Intelligence (AI) augmented Mobile Ad Hoc Networks (MANETs) based real-time prediction paradigm for urban traffic challenges. MANETs are wireless networks that are based on mobile devices and may self-organize. The distributed nature of MANETs and the power of AI approaches are leveraged in this framework to provide reliable and timely traffic congestion forecasts. This study suggests a unique Chaotic Spatial Fuzzy Polynomial Neural Network (CSFPNN) technique to assess real-time data… More >

  • Open Access

    ARTICLE

    A Dual Discriminator Method for Generalized Zero-Shot Learning

    Tianshu Wei1, Jinjie Huang1,2,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1599-1612, 2024, DOI:10.32604/cmc.2024.048098

    Abstract Zero-shot learning enables the recognition of new class samples by migrating models learned from semantic features and existing sample features to things that have never been seen before. The problems of consistency of different types of features and domain shift problems are two of the critical issues in zero-shot learning. To address both of these issues, this paper proposes a new modeling structure. The traditional approach mapped semantic features and visual features into the same feature space; based on this, a dual discriminator approach is used in the proposed model. This dual discriminator approach can… More >

  • Open Access

    ARTICLE

    A Novel Insertion Solution for the Travelling Salesman Problem

    Emmanuel Oluwatobi Asani1,2,3, Aderemi Elisha Okeyinka4, Sunday Adeola Ajagbe5,6, Ayodele Ariyo Adebiyi1, Roseline Oluwaseun Ogundokun1,2,7,*, Temitope Samson Adekunle8, Pragasen Mudali5, Matthew Olusegun Adigun5

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1581-1597, 2024, DOI:10.32604/cmc.2024.047898

    Abstract The study presents the Half Max Insertion Heuristic (HMIH) as a novel approach to solving the Travelling Salesman Problem (TSP). The goal is to outperform existing techniques such as the Farthest Insertion Heuristic (FIH) and Nearest Neighbour Heuristic (NNH). The paper discusses the limitations of current construction tour heuristics, focusing particularly on the significant margin of error in FIH. It then proposes HMIH as an alternative that minimizes the increase in tour distance and includes more nodes. HMIH improves tour quality by starting with an initial tour consisting of a ‘minimum’ polygon and iteratively adding… More >

  • Open Access

    REVIEW

    Review of Collocation Methods and Applications in Solving Science and Engineering Problems

    Weiwu Jiang1, Xiaowei Gao1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 41-76, 2024, DOI:10.32604/cmes.2024.048313

    Abstract The collocation method is a widely used numerical method for science and engineering problems governed by partial differential equations. This paper provides a comprehensive review of collocation methods and their applications, focused on elasticity, heat conduction, electromagnetic field analysis, and fluid dynamics. The merits of the collocation method can be attributed to the need for element mesh, simple implementation, high computational efficiency, and ease in handling irregular domain problems since the collocation method is a type of node-based numerical method. Beginning with the fundamental principles of the collocation method, the discretization process in the continuous… More >

  • Open Access

    ARTICLE

    Relationship between Authoritative Parenting Style and Preschool Children’s Emotion Regulation: A Moderated Mediation Model

    Yan Jin, Wei Chen*

    International Journal of Mental Health Promotion, Vol.26, No.3, pp. 189-198, 2024, DOI:10.32604/ijmhp.2023.045331

    Abstract An authoritative parenting style has been shown to promote children’s emotion regulation in European-American family studies. However, little is known about how sleep problems and the child’s sibling status in Chinese families affect this relationship. Based on family system theory, this study attempts to better understand the relationship between authoritative parenting style and emotion regulation. Mothers of preschool children in Chinese kindergartens completed questionnaires about their children’s sleep habits, their authoritative parenting styles, and children’s emotion regulation. A total of 531 children participated in this study. Results showed that authoritative parenting was positively associated with… More >

  • Open Access

    ARTICLE

    MOALG: A Metaheuristic Hybrid of Multi-Objective Ant Lion Optimizer and Genetic Algorithm for Solving Design Problems

    Rashmi Sharma1, Ashok Pal1, Nitin Mittal2, Lalit Kumar2, Sreypov Van3, Yunyoung Nam3,*, Mohamed Abouhawwash4,5

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3489-3510, 2024, DOI:10.32604/cmc.2024.046606

    Abstract This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm (MOALO) which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm (ALO) and the Genetic Algorithm (GA). MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated solutions. The uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO. A first-time hybrid of these… More >

  • Open Access

    ARTICLE

    Optimal Shape Factor and Fictitious Radius in the MQ-RBF: Solving Ill-Posed Laplacian Problems

    Chein-Shan Liu1, Chung-Lun Kuo1, Chih-Wen Chang2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3189-3208, 2024, DOI:10.32604/cmes.2023.046002

    Abstract To solve the Laplacian problems, we adopt a meshless method with the multiquadric radial basis function (MQ-RBF) as a basis whose center is distributed inside a circle with a fictitious radius. A maximal projection technique is developed to identify the optimal shape factor and fictitious radius by minimizing a merit function. A sample function is interpolated by the MQ-RBF to provide a trial coefficient vector to compute the merit function. We can quickly determine the optimal values of the parameters within a preferred rage using the golden section search algorithm. The novel method provides the More >

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