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  • Open Access


    Managing Health Treatment by Optimizing Complex Lab-Developed Test Configurations: A Health Informatics Perspective

    Uzma Afzal1, Tariq Mahmood2, Ali Mustafa Qamar3,*, Ayaz H. Khan4,5

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6251-6267, 2023, DOI:10.32604/cmc.2023.037653

    Abstract A complex Laboratory Developed Test (LDT) is a clinical test developed within a single laboratory. It is typically configured from many feature constraints from clinical repositories, which are part of the existing Laboratory Information Management System (LIMS). Although these clinical repositories are automated, support for managing patient information with test results of an LDT is also integrated within the existing LIMS. Still, the support to configure LDTs design needs to be made available even in standard LIMS packages. The manual configuration of LDTs is a complex process and can generate configuration inconsistencies because many constraints between features can remain unsatisfied.… More >

  • Open Access


    On Layout Optimization of Wireless Sensor Network Using Meta-Heuristic Approach

    Abeeda Akram1, Kashif Zafar1, Adnan Noor Mian2, Abdul Rauf Baig3, Riyad Almakki3, Lulwah AlSuwaidan3, Shakir Khan3,4,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3685-3701, 2023, DOI:10.32604/csse.2023.032024

    Abstract One of the important research issues in wireless sensor networks (WSNs) is the optimal layout designing for the deployment of sensor nodes. It directly affects the quality of monitoring, cost, and detection capability of WSNs. Layout optimization is an NP-hard combinatorial problem, which requires optimization of multiple competing objectives like cost, coverage, connectivity, lifetime, load balancing, and energy consumption of sensor nodes. In the last decade, several meta-heuristic optimization techniques have been proposed to solve this problem, such as genetic algorithms (GA) and particle swarm optimization (PSO). However, these approaches either provided computationally expensive solutions or covered a limited number… More >

  • Open Access


    An Optimization Capacity Design Method of Wind/Photovoltaic/Hydrogen Storage Power System Based on PSO-NSGA-II

    Lei Xing1, Yakui Liu2,3,*

    Energy Engineering, Vol.120, No.4, pp. 1023-1043, 2023, DOI:10.32604/ee.2023.025335

    Abstract The optimal allocation of integrated energy system capacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption of renewable energy, which has attracted many attentions. However, the optimization results of heuristic algorithms are usually influenced by the choice of hyperparameters. To solve the above problem, the particle swarm algorithm is introduced to find the optimal hyperparameters of the heuristic algorithms. Firstly, an integrated energy system consisting of the photovoltaic, wind turbine, electrolysis cell, hydrogen storage tank, and energy storage is established. Meanwhile, the minimum economic cost, the maximum wind and PV power consumption rate, and the… More >

  • Open Access


    Vehicle Plate Number Localization Using Memetic Algorithms and Convolutional Neural Networks

    Gibrael Abosamra*

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3539-3560, 2023, DOI:10.32604/cmc.2023.032976

    Abstract This paper introduces the third enhanced version of a genetic algorithm-based technique to allow fast and accurate detection of vehicle plate numbers (VPLN) in challenging image datasets. Since binarization of the input image is the most important and difficult step in the detection of VPLN, a hybrid technique is introduced that fuses the outputs of three fast techniques into a pool of connected components objects (CCO) and hence enriches the solution space with more solution candidates. Due to the combination of the outputs of the three binarization techniques, many CCOs are produced into the output pool from which one or… More >

  • Open Access


    Generating of Test Data by Harmony Search Against Genetic Algorithms

    Ahmed S. Ghiduk1,2,*, Abdullah Alharbi1

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 647-665, 2023, DOI:10.32604/iasc.2023.031865

    Abstract Many search-based algorithms have been successfully applied in several software engineering activities. Genetic algorithms (GAs) are the most used in the scientific domains by scholars to solve software testing problems. They imitate the theory of natural selection and evolution. The harmony search algorithm (HSA) is one of the most recent search algorithms in the last years. It imitates the behavior of a musician to find the best harmony. Scholars have estimated the similarities and the differences between genetic algorithms and the harmony search algorithm in diverse research domains. The test data generation process represents a critical task in software validation.… More >

  • Open Access


    Value-Based Test Case Prioritization for Regression Testing Using Genetic Algorithms

    Farrukh Shahzad Ahmed, Awais Majeed, Tamim Ahmed Khan*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2211-2238, 2023, DOI:10.32604/cmc.2023.032664

    Abstract Test Case Prioritization (TCP) techniques perform better than other regression test optimization techniques including Test Suite Reduction (TSR) and Test Case Selection (TCS). Many TCP techniques are available, and their performance is usually measured through a metric Average Percentage of Fault Detection (APFD). This metric is value-neutral because it only works well when all test cases have the same cost, and all faults have the same severity. Using APFD for performance evaluation of test case orders where test cases cost or faults severity varies is prone to produce false results. Therefore, using the right metric for performance evaluation of TCP… More >

  • Open Access


    Hybrid Global Optimization Algorithm for Feature Selection

    Ahmad Taher Azar1,2,*, Zafar Iqbal Khan2, Syed Umar Amin2, Khaled M. Fouad1,3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2021-2037, 2023, DOI:10.32604/cmc.2023.032183

    Abstract This paper proposes Parallelized Linear Time-Variant Acceleration Coefficients and Inertial Weight of Particle Swarm Optimization algorithm (PLTVACIW-PSO). Its designed has introduced the benefits of Parallel computing into the combined power of TVAC (Time-Variant Acceleration Coefficients) and IW (Inertial Weight). Proposed algorithm has been tested against linear, non-linear, traditional, and multiswarm based optimization algorithms. An experimental study is performed in two stages to assess the proposed PLTVACIW-PSO. Phase I uses 12 recognized Standard Benchmarks methods to evaluate the comparative performance of the proposed PLTVACIW-PSO vs. IW based Particle Swarm Optimization (PSO) algorithms, TVAC based PSO algorithms, traditional PSO, Genetic algorithms (GA),… More >

  • Open Access


    Hybrid Optimization Based PID Controller Design for Unstable System

    Saranya Rajeshwaran1,*, C. Agees Kumar2, Kanthaswamy Ganapathy3

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1611-1625, 2023, DOI:10.32604/iasc.2023.029299

    Abstract PID controllers play an important function in determining tuning parameters in any process sector to deliver optimal and resilient performance for nonlinear, stable and unstable processes. The effectiveness of the presented hybrid metaheuristic algorithms for a class of time-delayed unstable systems is described in this study when applicable to the problems of PID controller and Smith PID controller. The Direct Multi Search (DMS) algorithm is utilised in this research to combine the local search ability of global heuristic algorithms to tune a PID controller for a time-delayed unstable process model. A Metaheuristics Algorithm such as, SA (Simulated Annealing), MBBO (Modified… More >

  • Open Access


    Generating Intelligent Remedial Materials with Genetic Algorithms and Concept Maps

    Che-Chern Lin*, Chien-Chun Pan

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1333-1349, 2022, DOI:10.32604/iasc.2022.025387

    Abstract This study proposes an intelligent remedial learning framework to improve students’ learning effectiveness. Basically, this framework combines a genetic algorithm with a concept map in order to select a set of remedial learning units according to students’ weaknesses of learning concepts. In the proposed algorithm, a concept map serves to represent the knowledge structure of learning concepts, and a genetic algorithm performs an iteratively evolutionary procedure in order to establish remedial learning materials based on students’ understanding of these learning concepts. This study also conducted simulations in order to validate the proposed framework using artificially generated data sets, and problematic… More >

  • Open Access


    Numerical Solutions of a Novel Designed Prevention Class in the HIV Nonlinear Model

    Zulqurnain Sabir1, Muhammad Umar1, Muhammad Asif Zahoor Raja2,*, Dumitru Baleanu3,4

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 227-251, 2021, DOI:10.32604/cmes.2021.016611

    Abstract The presented research aims to design a new prevention class (P) in the HIV nonlinear system, i.e., the HIPV model. Then numerical treatment of the newly formulated HIPV model is portrayed handled by using the strength of stochastic procedure based numerical computing schemes exploiting the artificial neural networks (ANNs) modeling legacy together with the optimization competence of the hybrid of global and local search schemes via genetic algorithms (GAs) and active-set approach (ASA), i.e., GA-ASA. The optimization performances through GA-ASA are accessed by presenting an error-based fitness function designed for all the classes of the HIPV model and its corresponding… More >

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