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  • Open Access

    ARTICLE

    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 >

  • Open Access

    ARTICLE

    A survey on the Metaheuristics for Cryptanalysis of Substitution and Transposition Ciphers

    Arkan Kh Shakr Sabonchi*, Bahriye Akay

    Computer Systems Science and Engineering, Vol.39, No.1, pp. 87-106, 2021, DOI:10.32604/csse.2021.05365

    Abstract This paper presents state-of-art cryptanalysis studies on attacks of the substitution and transposition ciphers using various metaheuristic algorithms. Traditional cryptanalysis methods employ an exhaustive search, which is computationally expensive. Therefore, metaheuristics have attracted the interest of researchers in the cryptanalysis field. Metaheuristic algorithms are known for improving the search for the optimum solution and include Genetic Algorithm, Simulated Annealing, Tabu Search, Particle Swarm Optimization, Differential Evolution, Ant Colony, the Artificial Bee Colony, Cuckoo Search, and Firefly algorithms. The most important part of these various applications is deciding the fitness function to guide the search. This review presents how these algorithms… More >

  • Open Access

    ARTICLE

    A Hybrid Model Using Bio-Inspired Metaheuristic Algorithms for Network Intrusion Detection System

    Omar Almomani*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 409-429, 2021, DOI:10.32604/cmc.2021.016113

    Abstract Network Intrusion Detection System (IDS) aims to maintain computer network security by detecting several forms of attacks and unauthorized uses of applications which often can not be detected by firewalls. The features selection approach plays an important role in constructing effective network IDS. Various bio-inspired metaheuristic algorithms used to reduce features to classify network traffic as abnormal or normal traffic within a shorter duration and showing more accuracy. Therefore, this paper aims to propose a hybrid model for network IDS based on hybridization bio-inspired metaheuristic algorithms to detect the generic attack. The proposed model has two objectives; The first one… 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

    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

    Hybrid Clustering Algorithms with GRASP to Construct an Initial Solution for the MVPPDP

    Abeer I. Alhujaylan1, 2, *, Manar I. Hosny1

    CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1025-1051, 2020, DOI:10.32604/cmc.2020.08742

    Abstract Mobile commerce (m-commerce) contributes to increasing the popularity of electronic commerce (e-commerce), allowing anybody to sell or buy goods using a mobile device or tablet anywhere and at any time. As demand for e-commerce increases tremendously, the pressure on delivery companies increases to organise their transportation plans to achieve profits and customer satisfaction. One important planning problem in this domain is the multi-vehicle profitable pickup and delivery problem (MVPPDP), where a selected set of pickup and delivery customers need to be served within certain allowed trip time. In this paper, we proposed hybrid clustering algorithms with the greedy randomised adaptive… More >

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