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Search Results (42)
  • Open Access

    ARTICLE

    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… More >

  • Open Access

    ARTICLE

    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,… More >

  • Open Access

    ARTICLE

    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 More >

  • Open Access

    ARTICLE

    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 More >

  • Open Access

    ARTICLE

    Optimization of the Active Composition of the Wind Farm Using Genetic Algorithms

    Nataliya Shakhovska1,*, Mykola Medykovskyy2, Roman Melnyk2, Nataliya Kryvinska3

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3065-3078, 2021, DOI:10.32604/cmc.2021.018761

    Abstract The article presents the results of research on the possibilities of using genetic algorithms for solving the multicriteria optimization problem of determining the active components of a wind farm. Optimization is carried out on two parameters: efficiency factor of wind farm use (integrated parameter calculated on the basis of 6 parameters of each of the wind farm), average power deviation level (average difference between the load power and energy generation capabilities of the active wind farm). That was done an analysis of publications on the use of genetic algorithms to solve multicriteria optimization problems. Computer… More >

  • Open Access

    ARTICLE

    Task Scheduling Optimization in Cloud Computing Based on Genetic Algorithms

    Ahmed Y. Hamed1,*, Monagi H. Alkinani2

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3289-3301, 2021, DOI:10.32604/cmc.2021.018658

    Abstract Task scheduling is the main problem in cloud computing that reduces system performance; it is an important way to arrange user needs and perform multiple goals. Cloud computing is the most popular technology nowadays and has many research potential in various areas like resource allocation, task scheduling, security, privacy, etc. To improve system performance, an efficient task-scheduling algorithm is required. Existing task-scheduling algorithms focus on task-resource requirements, CPU memory, execution time, and execution cost. In this paper, a task scheduling algorithm based on a Genetic Algorithm (GA) has been presented for assigning and executing different… More >

  • Open Access

    ARTICLE

    Robust Optimal Proportional–Integral Controller for an Uncertain Unstable Delay System: Wind Process Application

    Rihem Farkh1,2, Yasser Fouad1,*, Haykel Marouani1

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 837-851, 2021, DOI:10.32604/iasc.2021.018214

    Abstract In industrial practice, certain processes are unstable, such as different types of reactors, distillation columns, and combustion systems. To ensure greater maneuverability and improve the speed of response command, certain systems in the military and aviation fields are purposely configured to be unstable. These systems are often more difficult to control than stable systems and are of particular interest to designers and control engineers. Despite all advances in process control over the past six decades, the proportional–integral–derivative (PID) controller is still the most common. The main reasons are the simplicity, robustness, and successful applications provided… More >

  • Open Access

    ARTICLE

    A Hybrid Scheme for Secure Wireless Communications in IoT

    Muhammad Irshad Nazeer1,2,*, Ghulam Ali Mallah1, Raheel Ahmed Memon2

    Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 633-648, 2021, DOI:10.32604/iasc.2021.017771

    Abstract Network Coding is a potential technology for the future wireless communications and Internet of Things (IoT) as it reduces the number of transmissions and offers energy efficiency. It is vulnerable to threat and attack that can harm intermediate nodes. Indeed, it exhibits an ability to incorporate security of transmitted data, yet a lot of work needs to be done to provide a safeguard from threats. The purpose of this study is to strengthen the existing Network Coding scheme with a set of generic requirements for Network Coding Protocols by adopting system models and a Genetic… More >

  • Open Access

    ARTICLE

    Parallel Optimization of Program Instructions Using Genetic Algorithms

    Petre Anghelescu*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3293-3310, 2021, DOI:10.32604/cmc.2021.015495

    Abstract This paper describes an efficient solution to parallelize software program instructions, regardless of the programming language in which they are written. We solve the problem of the optimal distribution of a set of instructions on available processors. We propose a genetic algorithm to parallelize computations, using evolution to search the solution space. The stages of our proposed genetic algorithm are: The choice of the initial population and its representation in chromosomes, the crossover, and the mutation operations customized to the problem being dealt with. In this paper, genetic algorithms are applied to the entire search… More >

  • Open Access

    ARTICLE

    Optimal Robust Control for Unstable Delay System

    Rihem Farkh1,2,*, Khaled A. Aljaloud1, Moufida Ksouri2, Faouzi Bouani2

    Computer Systems Science and Engineering, Vol.36, No.2, pp. 307-321, 2021, DOI:10.32604/csse.2021.014334

    Abstract Proportional-Integral-Derivative control system has been widely used in industrial applications. For uncertain and unstable systems, tuning controller parameters to satisfy the process requirements is very challenging. In general, the whole system’s performance strongly depends on the controller’s efficiency and hence the tuning process plays a key role in the system’s response. This paper presents a robust optimal Proportional-Integral-Derivative controller design methodology for the control of unstable delay system with parametric uncertainty using a combination of Kharitonov theorem and genetic algorithm optimization based approaches. In this study, the Generalized Kharitonov Theorem (GKT) for quasi-polynomials is employed… More >

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