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  • Open Access

    ARTICLE

    Optimal Intelligent Reconfiguration of Distribution Network in the Presence of Distributed Generation and Storage System

    Gang Lei1,*, Chunxiang Xu2

    Energy Engineering, Vol.119, No.5, pp. 2005-2029, 2022, DOI:10.32604/ee.2022.021154

    Abstract In the present paper, the distribution feeder reconfiguration in the presence of distributed generation resources (DGR) and energy storage systems (ESS) is solved in the dynamic form. Since studies on the reconfiguration problem have ignored the grid security and reliability, the non-distributed energy index along with the energy loss and voltage stability indices has been assumed as the objective functions of the given problem. To achieve the mentioned benefits, there are several practical plans in the distribution network. One of these applications is the network rearrangement plan, which is the simplest and least expensive way to add equipment to the… 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, SA (Simulated Annealing), MBBO (Modified… More >

  • Open Access

    ARTICLE

    Fault Diagnosis in Robot Manipulators Using SVM and KNN

    D. Maincer1,*, Y. Benmahamed2, M. Mansour1, Mosleh Alharthi3, Sherif S. M. Ghonein3

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1957-1969, 2023, DOI:10.32604/iasc.2023.029210

    Abstract In this paper, Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) based methods are to be applied on fault diagnosis in a robot manipulator. A comparative study between the two classifiers in terms of successfully detecting and isolating the seven classes of sensor faults is considered in this work. For both classifiers, the torque, the position and the speed of the manipulator have been employed as the input vector. However, it is to mention that a large database is needed and used for the training and testing phases. The SVM method used in this paper is based on the Gaussian… More >

  • Open Access

    ARTICLE

    Optimized Neural Network-Based Micro Strip Patch Antenna Design for Radar Application

    A. Yogeshwaran1,*, K. Umadevi2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1491-1503, 2023, DOI:10.32604/iasc.2023.026424

    Abstract Microstrip antennas are low-profile antennas that are utilized in wireless communication systems. In recent years, communication engineers have been increasingly interested in it. Because of downsizing, novelty, and cost reduction, the number of wireless standards has expanded in recent years. Wideband technologies have evolved in addition to analog and digital services. Radars necessitate antenna subsystems that are low-profile and lightweight. Microstrip antennas have these qualities and are suited for radars as an alternative to the bulky and heavyweight reflector/slotted waveguide array antennas. A perforated corner single-line fed microstrip antenna is designed here. When compared to the basic square microstrip antenna,… More >

  • Open Access

    ARTICLE

    Enhanced Long Short Term Memory for Early Alzheimer's Disease Prediction

    M. Vinoth Kumar1,*, M. Prakash2, M. Naresh Kumar3, H. Abdul Shabeer4

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1277-1293, 2023, DOI:10.32604/iasc.2023.025591

    Abstract The most noteworthy neurodegenerative disorder nationwide is apparently the Alzheimer's disease (AD) which ha no proven viable treatment till date and despite the clinical trials showing the potential of preclinical therapy, a sensitive method for evaluating the AD has to be developed yet. Due to the correlations between ocular and brain tissue, the eye (retinal blood vessels) has been investigated for predicting the AD. Hence, en enhanced method named Enhanced Long Short Term Memory (E-LSTM) has been proposed in this work which aims at finding the severity of AD from ocular biomarkers. To find the level of disease severity, the… More >

  • Open Access

    ARTICLE

    Performance Analysis of Optimization Based FOC and DTC Methods for Three Phase Induction Motor

    V. Jesus Bobin*, M. MarsalineBeno

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2493-2511, 2023, DOI:10.32604/iasc.2023.024679

    Abstract Three-phase induction motors are becoming increasingly utilized in industrial field due to their better efficiency and simple manufacture. The speed control of an induction motor is essential in a variety of applications, but it is difficult to control. This research analyses the three-phase induction motor’s performance using field-oriented control (FOC) and direct torque control (DTC) techniques. The major aim of this work is to provide a critical evaluation of developing a simple speed controller for induction motors with improving the performance of Induction Motor (IM). For controlling a motor, different optimization approaches are accessible; in this research, a Fuzzy Logic… More >

  • Open Access

    ARTICLE

    Multi-Layer and Multi-Objective Optimization Design of Supporting Structure of Large-Scale Spherical Solar Concentrator for the Space Solar Power Station

    Yang Yang, Jun Hu, Lin Zhu*, Mengchen Pei

    Journal of Renewable Materials, Vol.10, No.11, pp. 2835-2849, 2022, DOI:10.32604/jrm.2022.021840

    Abstract Space solar power station is a novel renewable energy equipment in space to provide the earth with abundant and continuous power. The Orb-shaped Membrane Energy Gathering Array, one of the alternative construction schemes in China, is promising for collecting space sunlight with a large-scale spherical concentrator. Both the structural and optical performances such as root mean square deformation, natural frequency, system mass, and sunlight blocking rate have significant influences on the system property of the concentrator. Considering the comprehensive performance of structure and optic, this paper proposes a novel mesh grid based on normal polyhedron projection and spherical arc bisection… More > Graphic Abstract

    Multi-Layer and Multi-Objective Optimization Design of Supporting Structure of Large-Scale Spherical Solar Concentrator for the Space Solar Power Station

  • Open Access

    ARTICLE

    Metaheuristic Optimization Through Deep Learning Classification of COVID-19 in Chest X-Ray Images

    Nagwan Abdel Samee1, El-Sayed M. El-Kenawy2,3, Ghada Atteia1,*, Mona M. Jamjoom4, Abdelhameed Ibrahim5, Abdelaziz A. Abdelhamid6,7, Noha E. El-Attar8, Tarek Gaber9,10, Adam Slowik11, Mahmoud Y. Shams12

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4193-4210, 2022, DOI:10.32604/cmc.2022.031147

    Abstract As corona virus disease (COVID-19) is still an ongoing global outbreak, countries around the world continue to take precautions and measures to control the spread of the pandemic. Because of the excessive number of infected patients and the resulting deficiency of testing kits in hospitals, a rapid, reliable, and automatic detection of COVID-19 is in extreme need to curb the number of infections. By analyzing the COVID-19 chest X-ray images, a novel metaheuristic approach is proposed based on hybrid dipper throated and particle swarm optimizers. The lung region was segmented from the original chest X-ray images and augmented using various… More >

  • Open Access

    ARTICLE

    A Hybrid Particle Swarm Optimization to Forecast Implied Volatility Risk

    Kais Tissaoui1,2,*, Sahbi Boubaker3,4, Waleed Saud Alghassab1, Taha Zaghdoudi1,5, Jamel Azibi6

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4291-4309, 2022, DOI:10.32604/cmc.2022.028830

    Abstract The application of optimization methods to prediction issues is a continually exploring field. In line with this, this paper investigates the connectedness between the infected cases of COVID-19 and US fear index from a forecasting perspective. The complex characteristics of implied volatility risk index such as non-linearity structure, time-varying and non-stationarity motivate us to apply a nonlinear polynomial Hammerstein model with known structure and unknown parameters. We use the Hybrid Particle Swarm Optimization (HPSO) tool to identify the model parameters of nonlinear polynomial Hammerstein model. Findings indicate that, following a nonlinear polynomial behaviour cascaded to an autoregressive with exogenous input… More >

  • Open Access

    ARTICLE

    Email Filtering Using Hybrid Feature Selection Model

    Adel Hamdan Mohammad1,* , Sami Smadi2, Tariq Alwada’n3

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 435-450, 2022, DOI:10.32604/cmes.2022.020088

    Abstract Undoubtedly, spam is a serious problem, and the number of spam emails is increased rapidly. Besides, the massive number of spam emails prompts the need for spam detection techniques. Several methods and algorithms are used for spam filtering. Also, some emergent spam detection techniques use machine learning methods and feature extraction. Some methods and algorithms have been introduced for spam detecting and filtering. This research proposes two models for spam detection and feature selection. The first model is evaluated with the email spam classification dataset, which is based on reducing the number of keywords to its minimum. The results of… More >

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