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  • Open Access

    ARTICLE

    Optimizing Steering Angle Predictive Convolutional Neural Network for Autonomous Car

    Hajira Saleem1, Faisal Riaz1, Asadullah Shaikh2, Khairan Rajab2,3, Adel Rajab2,*, Muhammad Akram2, Mana Saleh Al Reshan2

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2285-2302, 2022, DOI:10.32604/cmc.2022.022726

    Abstract Deep learning techniques, particularly convolutional neural networks (CNNs), have exhibited remarkable performance in solving vision-related problems, especially in unpredictable, dynamic, and challenging environments. In autonomous vehicles, imitation-learning-based steering angle prediction is viable due to the visual imagery comprehension of CNNs. In this regard, globally, researchers are currently focusing on the architectural design and optimization of the hyperparameters of CNNs to achieve the best results. Literature has proven the superiority of metaheuristic algorithms over the manual-tuning of CNNs. However, to the best of our knowledge, these techniques are yet to be applied to address the problem of imitation-learning-based steering angle prediction.… More >

  • Open Access

    ARTICLE

    Energy Aware Metaheuristic Optimization with Location Aided Routing Protocol for MANET

    E. Ahila Devi1, K. C. Ramya2, K. Sathesh Kumar3, Sultan Ahmad4, Seifedine Kadry5, Hyung Ju Park6, Byeong-Gwon Kang6,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1567-1580, 2022, DOI:10.32604/cmc.2022.022539

    Abstract A mobile ad hoc network (MANET) involves a group of wireless mobile nodes which create an impermanent network with no central authority and infrastructure. The nodes in the MANET are highly mobile and it results in adequate network topology, link loss, and increase the re-initialization of the route discovery process. Route planning in MANET is a multi-hop communication process due to the restricted transmission range of the nodes. Location aided routing (LAR) is one of the effective routing protocols in MANET which suffers from the issue of high energy consumption. Though few research works have focused on resolving energy consumption… More >

  • Open Access

    ARTICLE

    Reliability Analysis of Piled Raft Foundation Using a Novel Hybrid Approach of ANN and Equilibrium Optimizer

    Abidhan Bardhan1, Priyadip Manna1, Vinay Kumar1, Avijit Burman1, Bojan Žlender2, Pijush Samui1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1033-1067, 2021, DOI:10.32604/cmes.2021.015885

    Abstract In many civil engineering projects, Piled Raft Foundations (PRFs) are usually preferred where the incoming load from the superstructures is very high. In geotechnical engineering practice, the settlement of soil layers is a critical issue for the serviceability of the structures. Thus, assessment of risk associated with the structures corresponding to the maximum allowable settlement of soils needs to be carried out in the design phase. In this study, reliability analysis of PRF based on settlement criteria is performed using a high-performance hybrid soft computing model. The new approach is an integration of the artificial neural network (ANN) and a… More >

  • Open Access

    ARTICLE

    Managing Delivery of Safeguarding Substances as a Mitigation Against Outbreaks of Pandemics

    Said Ali Hassan1, Khalid Alnowibet2,3, Prachi Agrawal4, Ali Wagdy Mohamed5,6,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1161-1181, 2021, DOI:10.32604/cmc.2021.015494

    Abstract The optimum delivery of safeguarding substances is a major part of supply chain management and a crucial issue in the mitigation against the outbreak of pandemics. A problem arises for a decision maker who wants to optimally choose a subset of candidate consumers to maximize the distributed quantities of the needed safeguarding substances within a specific time period. A nonlinear binary mathematical programming model for the problem is formulated. The decision variables are binary ones that represent whether to choose a specific consumer, and design constraints are formulated to keep track of the chosen route. To better illustrate the problem,… More >

  • Open Access

    ARTICLE

    Rock Hyraxes Swarm Optimization: A New Nature-Inspired Metaheuristic Optimization Algorithm

    Belal Al-Khateeb1,*, Kawther Ahmed2, Maha Mahmood1, Dac-Nhuong Le3,4

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 643-654, 2021, DOI:10.32604/cmc.2021.013648

    Abstract This paper presents a novel metaheuristic algorithm called Rock Hyraxes Swarm Optimization (RHSO) inspired by the behavior of rock hyraxes swarms in nature. The RHSO algorithm mimics the collective behavior of Rock Hyraxes to find their eating and their special way of looking at this food. Rock hyraxes live in colonies or groups where a dominant male watch over the colony carefully to ensure their safety leads the group. Forty-eight (22 unimodal and 26 multimodal) test functions commonly used in the optimization area are used as a testing benchmark for the RHSO algorithm. A comparative efficiency analysis also checks RHSO… More >

  • Open Access

    ARTICLE

    A New Metaheuristic Optimization Algorithms for Brushless Direct Current Wheel Motor Design Problem

    M. Premkumar1, R. Sowmya2, Pradeep Jangir3, Kottakkaran Sooppy Nisar4,*, Mujahed Aldhaifallah5

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2227-2242, 2021, DOI:10.32604/cmc.2021.015565

    Abstract The Equilibrium Optimizer (EO), Grey Wolf Optimizer (GWO), and Whale Optimizer (WO) algorithms are being recently developed for engineering optimization problems. In this paper, the EO, GWO, and WO algorithms are applied individually for a brushless direct current (BLDC) design optimization problem. The EO algorithm is inspired by the models utilized to find the system’s dynamic state and equilibrium state. The GWO and WO algorithms are inspired by the hunting behavior of the wolf and the whale, respectively. The primary purpose of any optimization technique is to find the optimal configuration by maximizing motor efficiency and/or minimizing the total mass.… More >

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