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  • Open Access

    ARTICLE

    Solar Radiation Estimation Based on a New Combined Approach of Artificial Neural Networks (ANN) and Genetic Algorithms (GA) in South Algeria

    Djeldjli Halima1,*, Benatiallah Djelloul1, Ghasri Mehdi2, Tanougast Camel3, Benatiallah Ali4, Benabdelkrim Bouchra1

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4725-4740, 2024, DOI:10.32604/cmc.2024.051002

    Abstract When designing solar systems and assessing the effectiveness of their many uses, estimating sun irradiance is a crucial first step. This study examined three approaches (ANN, GA-ANN, and ANFIS) for estimating daily global solar radiation (GSR) in the south of Algeria: Adrar, Ouargla, and Bechar. The proposed hybrid GA-ANN model, based on genetic algorithm-based optimization, was developed to improve the ANN model. The GA-ANN and ANFIS models performed better than the standalone ANN-based model, with GA-ANN being better suited for forecasting in all sites, and it performed the best with the best values in the… More > Graphic Abstract

    Solar Radiation Estimation Based on a New Combined Approach of Artificial Neural Networks (ANN) and Genetic Algorithms (GA) in South Algeria

  • Open Access

    ARTICLE

    Appropriate Combination of Crossover Operator and Mutation Operator in Genetic Algorithms for the Travelling Salesman Problem

    Zakir Hussain Ahmed1,*, Habibollah Haron2, Abdullah Al-Tameem3

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2399-2425, 2024, DOI:10.32604/cmc.2024.049704

    Abstract Genetic algorithms (GAs) are very good metaheuristic algorithms that are suitable for solving NP-hard combinatorial optimization problems. A simple GA begins with a set of solutions represented by a population of chromosomes and then uses the idea of survival of the fittest in the selection process to select some fitter chromosomes. It uses a crossover operator to create better offspring chromosomes and thus, converges the population. Also, it uses a mutation operator to explore the unexplored areas by the crossover operator, and thus, diversifies the GA search space. A combination of crossover and mutation operators… More >

  • Open Access

    ARTICLE

    Optimizing Region of Interest Selection for Effective Embedding in Video Steganography Based on Genetic Algorithms

    Nizheen A. Ali1, Ramadhan J. Mstafa2,3,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1451-1469, 2023, DOI:10.32604/csse.2023.039957

    Abstract With the widespread use of the internet, there is an increasing need to ensure the security and privacy of transmitted data. This has led to an intensified focus on the study of video steganography, which is a technique that hides data within a video cover to avoid detection. The effectiveness of any steganography method depends on its ability to embed data without altering the original video’s quality while maintaining high efficiency. This paper proposes a new method to video steganography, which involves utilizing a Genetic Algorithm (GA) for identifying the Region of Interest (ROI) in… More >

  • Open Access

    ARTICLE

    Multi-Objective Optimization of Traffic Signal Timing at Typical Junctions Based on Genetic Algorithms

    Zeyu Zhang1, Han Zhu1, Wei Zhang1, Zhiming Cai2,*, Linkai Zhu2, Zefeng Li2

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1901-1917, 2023, DOI:10.32604/csse.2023.039395

    Abstract With the rapid development of urban road traffic and the increasing number of vehicles, how to alleviate traffic congestion is one of the hot issues that need to be urgently addressed in building smart cities. Therefore, in this paper, a nonlinear multi-objective optimization model of urban intersection signal timing based on a Genetic Algorithm was constructed. Specifically, a typical urban intersection was selected as the research object, and drivers’ acceleration habits were taken into account. What’s more, the shortest average delay time, the least average number of stops, and the maximum capacity of the intersection… More >

  • Open Access

    ARTICLE

    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… More >

  • Open Access

    ARTICLE

    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… More >

  • Open Access

    ARTICLE

    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… More >

  • Open Access

    ARTICLE

    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… More >

  • Open Access

    ARTICLE

    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… More >

  • Open Access

    ARTICLE

    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… More >

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