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Research Article

BEST PAPER 2021

Recent Advances in Metaheuristic Techniques and Their Real-World Applications


Submission Deadline: 25 August 2021 (closed)

Abstract

This article has no abstract.

Keywords

Deep learning, Metaheuristic, Explainable AI, Real-time applications
  • Research Article

    BEST PAPER 2021

    Hybrid Cuckoo Search Algorithm for Scheduling in Cloud Computing

    Manoj Kumar*, Suman CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1641-1660, 2022, DOI:10.32604/cmc.2022.021793
    Abstract Cloud computing has gained widespread popularity over the last decade. Scheduling problem in cloud computing is prejudiced due to enormous demands of cloud users. Meta-heuristic techniques in cloud computing have exhibited high performance in comparison to traditional scheduling algorithms. This paper presents a novel hybrid Nesterov Accelerated Gradient-based Cuckoo Search Algorithm (NAGCSA) to address the scheduling issue in cloud computing. Nesterov Accelerated Gradient can address trapping at local minima in CSA by updating the position using future approximation. The local search in the proposed algorithm is performed by using Nesterov Accelerated Gradient, while the global search is performed by using… More >

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  • Research Article

    BEST PAPER 2021

    Optimal Parameter Estimation of Transmission Line Using Chaotic Initialized Time-Varying PSO Algorithm

    Abdullah Shoukat1, Muhammad Ali Mughal1,*, Saifullah Younus Gondal1, Farhana Umer2, Tahir Ejaz3, Ashiq Hussain1 CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 269-285, 2022, DOI:10.32604/cmc.2022.021575
    Abstract Transmission line is a vital part of the power system that connects two major points, the generation, and the distribution. For an efficient design, stable control, and steady operation of the power system, adequate knowledge of the transmission line parameters resistance, inductance, capacitance, and conductance is of great importance. These parameters are essential for transmission network expansion planning in which a new parallel line is needed to be installed due to increased load demand or the overhead line is replaced with an underground cable. This paper presents a method to optimally estimate the parameters using the input-output quantities i.e., voltages,… More >

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  • Research Article

    BEST PAPER 2021

    ATS: A Novel Time-Sharing CPU Scheduling Algorithm Based on Features Similarities

    Samih M. Mostafa1,*, Sahar Ahmed Idris2, Manjit Kaur3 CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6271-6288, 2022, DOI:10.32604/cmc.2022.021978
    Abstract Minimizing time cost in time-shared operating systems is considered basic and essential task, and it is the most significant goal for the researchers who interested in CPU scheduling algorithms. Waiting time, turnaround time, and number of context switches are the most time cost criteria used to compare between CPU scheduling algorithms. CPU scheduling algorithms are divided into non-preemptive and preemptive. Round Robin (RR) algorithm is the most famous as it is the basis for all the algorithms used in time-sharing. In this paper, the authors proposed a novel CPU scheduling algorithm based on RR. The proposed algorithm is called Adjustable… More >

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  • Research Article

    BEST PAPER 2021

    Extremal Coalitions for Influence Games Through Swarm Intelligence-Based Methods

    Fabián Riquelme1,*, Rodrigo Olivares1, Francisco Muñoz1, Xavier Molinero3, Maria Serna2 CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6305-6321, 2022, DOI:10.32604/cmc.2022.021804
    Abstract An influence game is a simple game represented over an influence graph (i.e., a labeled, weighted graph) on which the influence spread phenomenon is exerted. Influence games allow applying different properties and parameters coming from cooperative game theory to the contexts of social network analysis, decision-systems, voting systems, and collective behavior. The exact calculation of several of these properties and parameters is computationally hard, even for a small number of players. Two examples of these parameters are the length and the width of a game. The length of a game is the size of its smaller winning coalition, while the… More >

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  • Research Article

    BEST PAPER 2021

    Semantic Information Extraction from Multi-Corpora Using Deep Learning

    Sunil Kumar1, Hanumat G. Sastry1, Venkatadri Marriboyina2, Hammam Alshazly3,*, Sahar Ahmed Idris4, Madhushi Verma5, Manjit Kaur5 CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5021-5038, 2022, DOI:10.32604/cmc.2022.021149
    Abstract Information extraction plays a vital role in natural language processing, to extract named entities and events from unstructured data. Due to the exponential data growth in the agricultural sector, extracting significant information has become a challenging task. Though existing deep learning-based techniques have been applied in smart agriculture for crop cultivation, crop disease detection, weed removal, and yield production, still it is difficult to find the semantics between extracted information due to unswerving effects of weather, soil, pest, and fertilizer data. This paper consists of two parts. An initial phase, which proposes a data preprocessing technique for removal of ambiguity… More >

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  • Research Article

    BEST PAPER 2021

    Position Control of Flexible Joint Carts Using Adaptive Generalized Dynamics Inversion

    Ibrahim M. Mehedi1,2,*, Mohd Heidir Mohd Shah1 , Soon Xin Ng3 , Abdulah Jeza Aljohani1,2, Mohammed El-Hajjar3, Muhammad Moinuddin1,2 CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4691-4705, 2022, DOI:10.32604/cmc.2022.020954
    Abstract

    This paper presents the design and implementation of Adaptive Generalized Dynamic Inversion (AGDI) to track the position of a Linear Flexible Joint Cart (LFJC) system along with vibration suppression of the flexible joint. The proposed AGDI control law will be comprised of two control elements. The baseline (continuous) control law is based on principle of conventional GDI approach and is established by prescribing the constraint dynamics of controlled state variables that reflect the control objectives. The control law is realized by inverting the prescribed dynamics using dynamically scaled Moore-Penrose generalized inversion. To boost the robust attributes against system nonlinearities, parametric… More >

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  • Research Article

    BEST PAPER 2021

    Fractional Order Linear Active Disturbance Rejection Control for Linear Flexible Joint System

    Ibrahim M. Mehedi1,2,*, Rachid Mansouri3, Ubaid M. Al-Saggaf1,2, Ahmed I. M. Iskanderani1, Maamar Bettayeb4, Abdulah Jeza Aljohani1,2, Thangam Palaniswamy1, Shaikh Abdul Latif5, Abdul Latif6 CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5133-5142, 2022, DOI:10.32604/cmc.2022.021018
    Abstract A linear flexible joint system using fractional order linear active disturbance rejection control is studied in this paper. With this control scheme, the performance against disturbances, uncertainties, and attenuation is enhanced. Linear active disturbance rejection control (LADRC) is mainly based on an extended state observer (ESO) technology. A fractional integral (FOI) action is combined with the LADRC technique which proposes a hybrid control scheme like FO-LADRC. Incorporating this FOI action improves the robustness of the standard LADRC. The set-point tracking of the proposed FO-LADRC scheme is designed by Bode's ideal transfer function (BITF) based robust closed-loop concept, an appropriate pole… More >

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  • Research Article

    BEST PAPER 2021

    MLA: A New Mutated Leader Algorithm for Solving Optimization Problems

    Fatemeh Ahmadi Zeidabadi1, Sajjad Amiri Doumari1, Mohammad Dehghani2, Zeinab Montazeri3, Pavel Trojovský4,*, Gaurav Dhiman5 CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5631-5649, 2022, DOI:10.32604/cmc.2022.021072
    Abstract Optimization plays an effective role in various disciplines of science and engineering. Optimization problems should either be optimized using the appropriate method (i.e., minimization or maximization). Optimization algorithms are one of the efficient and effective methods in providing quasi-optimal solutions for these type of problems. In this study, a new algorithm called the Mutated Leader Algorithm (MLA) is presented. The main idea in the proposed MLA is to update the members of the algorithm population in the search space based on the guidance of a mutated leader. In addition to information about the best member of the population, the mutated… More >

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  • Research Article

    BEST PAPER 2021

    Reactions’ Descriptors Selection and Yield Estimation Using Metaheuristic Algorithms and Voting Ensemble

    Olutomilayo Olayemi Petinrin1, Faisal Saeed2, Xiangtao Li1, Fahad Ghabban2, Ka-Chun Wong1,3,* CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4745-4762, 2022, DOI:10.32604/cmc.2022.020523
    Abstract Bioactive compounds in plants, which can be synthesized using N-arylation methods such as the Buchwald-Hartwig reaction, are essential in drug discovery for their pharmacological effects. Important descriptors are necessary for the estimation of yields in these reactions. This study explores ten metaheuristic algorithms for descriptor selection and model a voting ensemble for evaluation. The algorithms were evaluated based on computational time and the number of selected descriptors. Analyses show that robust performance is obtained with more descriptors, compared to cases where fewer descriptors are selected. The essential descriptor was deduced based on the frequency of occurrence within the 50 extracted… More >

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  • Research Article

    BEST PAPER 2021

    HARTIV: Human Activity Recognition Using Temporal Information in Videos

    Disha Deotale1, Madhushi Verma2, P. Suresh3, Sunil Kumar Jangir4, Manjit Kaur2, Sahar Ahmed Idris5, Hammam Alshazly6,* CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3919-3938, 2022, DOI:10.32604/cmc.2022.020655
    Abstract Nowadays, the most challenging and important problem of computer vision is to detect human activities and recognize the same with temporal information from video data. The video datasets are generated using cameras available in various devices that can be in a static or dynamic position and are referred to as untrimmed videos. Smarter monitoring is a historical necessity in which commonly occurring, regular, and out-of-the-ordinary activities can be automatically identified using intelligence systems and computer vision technology. In a long video, human activity may be present anywhere in the video. There can be a single or multiple human activities present… More >

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  • Research Article

    BEST PAPER 2021

    Speech Recognition-Based Automated Visual Acuity Testing with Adaptive Mel Filter Bank

    Shibli Nisar1, Muhammad Asghar Khan2,*, Fahad Algarni3, Abdul Wakeel1, M. Irfan Uddin4, Insaf Ullah2 CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2991-3004, 2022, DOI:10.32604/cmc.2022.020376
    Abstract One of the most commonly reported disabilities is vision loss, which can be diagnosed by an ophthalmologist in order to determine the visual system of a patient. This procedure, however, usually requires an appointment with an ophthalmologist, which is both time-consuming and expensive process. Other issues that can arise include a lack of appropriate equipment and trained practitioners, especially in rural areas. Centered on a cognitively motivated attribute extraction and speech recognition approach, this paper proposes a novel idea that immediately determines the eyesight deficiency. The proposed system uses an adaptive filter bank with weighted mel frequency cepstral coefficients for… More >

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