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  • Open Access

    ARTICLE

    Flower Pollination Heuristics for Nonlinear Active Noise Control Systems

    Wasim Ullah Khan1,*, Yigang He1, Muhammad Asif Zahoor Raja2, Naveed Ishtiaq Chaudhary3, Zeshan Aslam Khan3, Syed Muslim Shah4

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 815-834, 2021, DOI:10.32604/cmc.2021.014674

    Abstract Abstract In this paper, a novel design of the flower pollination algorithm is presented for model identification problems in nonlinear active noise control systems. The recently introduced flower pollination based heuristics is implemented to minimize the mean squared error based merit/cost function representing the scenarios of active noise control system with linear/nonlinear and primary/secondary paths based on the sinusoidal signal, random and complex random signals as noise interferences. The flower pollination heuristics based active noise controllers are formulated through exploitation of nonlinear filtering with Volterra series. The comparative study on statistical observations in terms of accuracy, convergence and complexity measures… More >

  • Open Access

    ARTICLE

    A New Database Intrusion Detection Approach Based on Hybrid Meta-Heuristics

    Youseef Alotaibi*

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1879-1895, 2021, DOI:10.32604/cmc.2020.013739

    Abstract A new secured database management system architecture using intrusion detection systems (IDS) is proposed in this paper for organizations with no previous role mapping for users. A simple representation of Structured Query Language queries is proposed to easily permit the use of the worked clustering algorithm. A new clustering algorithm that uses a tube search with adaptive memory is applied to database log files to create users’ profiles. Then, queries issued for each user are checked against the related user profile using a classifier to determine whether or not each query is malicious. The IDS will stop query execution or… More >

  • Open Access

    ARTICLE

    A Multi-objective Invasive Weed Optimization Method for Segmentation of Distress Images

    Eslam Mohammed Abdelkader1,2,*, Osama Moselhi3, Mohamed Marzouk4, Tarek Zayed5

    Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 643-661, 2020, DOI:10.32604/iasc.2020.010100

    Abstract Image segmentation is one of the fundamental stages in computer vision applications. Several meta-heuristics have been applied to solve the segmentation problems by extending the Otsu and entropy functions. However, no single-objective function can optimally handle the diversity of information in images besides the multimodality issues of gray-level images. This paper presents a self-adaptive multi-objective optimization-based method for the detection of crack images in reinforced concrete bridges. The proposed method combines the flexibility of information theory functions in addition to the invasive weed optimization algorithm for bi-level thresholding. The capabilities of the proposed method are demonstrated through comparisons with singleobjective… More >

  • Open Access

    ARTICLE

    A Novel Binary Firey Algorithm for the Minimum Labeling Spanning Tree Problem

    Mugang Lin1,2,*, Fangju Liu3, Huihuang Zhao1,2, Jianzhen Chen1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 197-214, 2020, DOI:10.32604/cmes.2020.09502

    Abstract Given a connected undirected graph G whose edges are labeled, the minimum labeling spanning tree (MLST) problem is to find a spanning tree of G with the smallest number of different labels. The MLST is an NP-hard combinatorial optimization problem, which is widely applied in communication networks, multimodal transportation networks, and data compression. Some approximation algorithms and heuristics algorithms have been proposed for the problem. Firey algorithm is a new meta-heuristic algorithm. Because of its simplicity and easy implementation, it has been successfully applied in various fields. However, the basic firefly algorithm for the MLST problem is proposed in this… 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 >

  • Open Access

    ARTICLE

    Comparative Study of Prey Predator Algorithm and Firefly Algorithm

    Hong Choon Onga, Surafel Luleseged Tilahunb, Wai Soon Leea, Jean Meadard T. Ngnotchouyeb

    Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 359-366, 2018, DOI:10.1080/10798587.2017.1294811

    Abstract Metaheuristic algorithms are found to be promising for difficult and high dimensional problems. Most of these algorithms are inspired by different natural phenomena. Currently, there are hundreds of these metaheuristic algorithms introduced and used. The introduction of new algorithm has been one of the issues researchers focused in the past fifteen years. However, there is a critic that some of the new algorithms are not in fact new in terms of their search behavior. Hence, a comparative study in between existing algorithms to highlight their differences and similarity needs to be studied. Apart from knowing the similarity and difference in… More >

  • Open Access

    ARTICLE

    QoS-Aware Energy-Efficient Task Scheduling on HPC Cloud Infrastructures Using Swarm-Intelligence Meta-Heuristics

    Amit Chhabra1, *, Gurvinder Singh2, Karanjeet Singh Kahlon2

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 813-834, 2020, DOI:10.32604/cmc.2020.010934

    Abstract Cloud computing infrastructure has been evolving as a cost-effective platform for providing computational resources in the form of high-performance computing as a service (HPCaaS) to users for executing HPC applications. However, the broader use of the Cloud services, the rapid increase in the size, and the capacity of Cloud data centers bring a remarkable rise in energy consumption leading to a significant rise in the system provider expenses and carbon emissions in the environment. Besides this, users have become more demanding in terms of Quality-of-service (QoS) expectations in terms of execution time, budget cost, utilization, and makespan. This situation calls… More >

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