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  • Open Access

    ARTICLE

    Control Strategy for a Quadrotor Based on a Memetic Shuffled Frog Leaping Algorithm

    Nour Ben Ammar1, Hegazy Rezk2,3,*, Soufiene Bouallègue1,4

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 4081-4100, 2021, DOI:10.32604/cmc.2021.015681

    Abstract This work presents a memetic Shuffled Frog Leaping Algorithm (SFLA) based tuning approach of an Integral Sliding Mode Controller (ISMC) for a quadrotor type of Unmanned Aerial Vehicles (UAV). Based on the Newton–Euler formalism, a nonlinear dynamic model of the studied quadrotor is firstly established for control design purposes. Since the main parameters of the ISMC design are the gains of the sliding surfaces and signum functions of the switching control law, which are usually selected by repetitive and time-consuming trials-errors based procedures, a constrained optimization problem is formulated for the systematically tuning of these unknown variables. Under time-domain operating… More >

  • Open Access

    ARTICLE

    A Novel IoT Application Recommendation System Using Metaheuristic Multi-Criteria Analysis

    Mohammed Hayder Kadhim, Farhad Mardukhi*

    Computer Systems Science and Engineering, Vol.37, No.2, pp. 149-158, 2021, DOI:10.32604/csse.2021.014608

    Abstract There are a variety of Internet of Things (IoT) applications that cover different aspects of daily life. Each of these applications has different criteria and sub-criteria, making it difficult for the user to choose. This requires an automated approach to select IoT applications by considering criteria. This paper presents a novel recommendation system for presenting applications on the IoT. First, using the analytic hierarchy process (AHP), a multi-layer architecture of the criteria and sub-criteria in IoT applications is presented. This architecture is used to evaluate and rank IoT applications. As a result, finding the weight of the criteria and sub-criteria… 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 >

  • Open Access

    ARTICLE

    Technology Landscape for Epidemiological Prediction and Diagnosis of COVID-19

    Siddhant Banyal1, Rinky Dwivedi2, Koyel Datta Gupta2, Deepak Kumar Sharma3,*, Fadi Al-Turjman4, Leonardo Mostarda5

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1679-1696, 2021, DOI:10.32604/cmc.2021.014387

    Abstract The COVID-19 outbreak initiated from the Chinese city of Wuhan and eventually affected almost every nation around the globe. From China, the disease started spreading to the rest of the world. After China, Italy became the next epicentre of the virus and witnessed a very high death toll. Soon nations like the USA became severely hit by SARS-CoV-2 virus. The World Health Organisation, on 11th March 2020, declared COVID-19 a pandemic. To combat the epidemic, the nations from every corner of the world has instituted various policies like physical distancing, isolation of infected population and researching on the potential vaccine… More >

  • Open Access

    ARTICLE

    Application of Metaheuristic Algorithms for Optimizing Longitudinal Square Porous Fins

    Samer H. Atawneh1, Waqar A. Khan2, Nawaf N. Hamadneh3,*, Adeeb M. Alhomoud3

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 73-87, 2021, DOI:10.32604/cmc.2021.012351

    Abstract The objectives of this study involve the optimization of longitudinal porous fins of square cross-section using metaheuristic algorithms. A generalized nonlinear ordinary differential equation is derived using Darcy and Fourier’s laws in the energy balance around a control volume and is solved numerically using RFK 45 method. The temperature of the base surface is higher than the fin surface, and the fin tip is kept adiabatic or cooled by convection heat transfer. The other pertinent parameters include Rayleigh number (100 ≤ Ra ≤ 104), Darcy number, (10−4 ≤ Da ≤ 10−2), relative thermal conductivity ratio of solid phase to fluid (1000 ≤ kr ≤ 8000), Nusselt number (10 ≤ Nu ≤ 100), porosity (0.1 ≤ φ ≤ 0.9).… More >

  • Open Access

    ARTICLE

    Metaheuristic Clustering Protocol for Healthcare Data Collection in Mobile Wireless Multimedia Sensor Networks

    G. Kadiravan1, P. Sujatha1, T. Asvany1, R. Punithavathi2, Mohamed Elhoseny3, Irina V. Pustokhina4, Denis A. Pustokhin5, K. Shankar6,*

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3215-3231, 2021, DOI:10.32604/cmc.2021.013034

    Abstract Nowadays, healthcare applications necessitate maximum volume of medical data to be fed to help the physicians, academicians, pathologists, doctors and other healthcare professionals. Advancements in the domain of Wireless Sensor Networks (WSN) and Multimedia Wireless Sensor Networks (MWSN) are tremendous. M-WMSN is an advanced form of conventional Wireless Sensor Networks (WSN) to networks that use multimedia devices. When compared with traditional WSN, the quantity of data transmission in M-WMSN is significantly high due to the presence of multimedia content. Hence, clustering techniques are deployed to achieve low amount of energy utilization. The current research work aims at introducing a new… More >

  • Open Access

    ARTICLE

    IWD-Miner: A Novel Metaheuristic Algorithm for Medical Data Classification

    Sarab AlMuhaideb*, Reem BinGhannam, Nourah Alhelal, Shatha Alduheshi, Fatimah Alkhamees, Raghad Alsuhaibani

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1329-1346, 2021, DOI:10.32604/cmc.2020.013576

    Abstract Medical data classification (MDC) refers to the application of classification methods on medical datasets. This work focuses on applying a classification task to medical datasets related to specific diseases in order to predict the associated diagnosis or prognosis. To gain experts’ trust, the prediction and the reasoning behind it are equally important. Accordingly, we confine our research to learn rule-based models because they are transparent and comprehensible. One approach to MDC involves the use of metaheuristic (MH) algorithms. Here we report on the development and testing of a novel MH algorithm: IWD-Miner. This algorithm can be viewed as a fusion… More >

  • Open Access

    ARTICLE

    Systematic Procedure for Optimal Controller Implementation Using Metaheuristic Algorithms

    Viorel Minzu*, Adrian Serbencu

    Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 663-677, 2020, DOI:10.32604/iasc.2020.010101

    Abstract The idea for this work starts from the situation in which a metaheuristic-based algorithm has already been developed in order to solve an optimal control problem. This algorithm yields an offline "optimal" solution. On the other hand, the Receding Horizon Control (RHC) structure can be implemented if a process model is available. This work underlines some of the practical aspects of joining the RHC to an existing metaheuristic-based algorithm in order to obtain a closed-loop control structure that can be further used in real-time control. The result is a systematic procedure that integrates a given metaheuristic-based algorithm into a RHC… More >

  • Open Access

    ARTICLE

    A Survey and Systematic Categorization of Parallel K-Means and Fuzzy-C-Means Algorithms

    Ahmed A. M. Jamel1,∗, Bahriye Akay2,†

    Computer Systems Science and Engineering, Vol.34, No.5, pp. 259-281, 2019, DOI:10.32604/csse.2019.34.259

    Abstract Parallel processing has turned into one of the emerging fields of machine learning due to providing consistent work by performing several tasks simultaneously, enhancing reliability (the presence of more than one device ensures the workflow even if some devices disrupted), saving processing time and introducing low cost and high-performance computation units. This research study presents a survey of parallel K-means and Fuzzy-c-means clustering algorithms based on their implementations in parallel environments such as Hadoop, MapReduce, Graphical Processing Units, and multi-core systems. Additionally, the enhancement in parallel clustering algorithms is investigated as hybrid approaches in which K-means and Fuzzy-c-means clustering algorithms… More >

  • Open Access

    ARTICLE

    A Multi-Objective Metaheuristics Study on Solving Constrained Relay Node Deployment Problem in WSNS

    Wenjie Yu, Xunbo Li, Hang Yang, Bo Huang

    Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 367-376, 2018, DOI:10.1080/10798587.2017.1294873

    Abstract This paper studies how to deploy relay nodes into traditional wireless sensor networks with constraint aiming to simultaneously optimize two important factors; average energy consumption and average network reliability. We consider tackling this multi-objective (MO) optimization problem with three metaheuristics, which employ greatly different evolutional strategies, and aim at an in-depth analysis of different performances of these metaheuristics to our problem. For this purpose, a statistical procedure is employed to analyse the results for confidence, in consideration of two MO quality metrics; hypervolume and coverage of two sets. After comprehensive analysis of the results, it is concluded that NSGA-II provides… More >

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