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  • Open Access

    ARTICLE

    Optimum Design for the Magnification Mechanisms Employing Fuzzy Logic–ANFIS

    Ngoc Thai Huynh1, Tien V. T. Nguyen2, Quoc Manh Nguyen3,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5961-5983, 2022, DOI:10.32604/cmc.2022.029484 - 28 July 2022

    Abstract To achieve high work performance for compliant mechanisms of motion scope, continuous work condition, and high frequency, we propose a new hybrid algorithm that could be applied to multi-objective optimum design. In this investigation, we use the tools of finite element analysis (FEA) for a magnification mechanism to find out the effects of design variables on the magnification ratio of the mechanism and then select an optimal mechanism that could meet design requirements. A poly-algorithm including the Grey-Taguchi method, fuzzy logic system, and adaptive neuro-fuzzy inference system (ANFIS) algorithm, was utilized mainly in this study.… More >

  • Open Access

    ARTICLE

    CNN Based Multi-Object Segmentation and Feature Fusion for Scene Recognition

    Adnan Ahmed Rafique1, Yazeed Yasin Ghadi2, Suliman A. Alsuhibany3, Samia Allaoua Chelloug4,*, Ahmad Jalal1, Jeongmin Park5

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4657-4675, 2022, DOI:10.32604/cmc.2022.027720 - 28 July 2022

    Abstract Latest advancements in vision technology offer an evident impact on multi-object recognition and scene understanding. Such scene-understanding task is a demanding part of several technologies, like augmented reality-based scene integration, robotic navigation, autonomous driving, and tourist guide. Incorporating visual information in contextually unified segments, convolution neural networks-based approaches will significantly mitigate the clutter, which is usual in classical frameworks during scene understanding. In this paper, we propose a convolutional neural network (CNN) based segmentation method for the recognition of multiple objects in an image. Initially, after acquisition and preprocessing, the image is segmented by using… More >

  • Open Access

    ARTICLE

    Evaluation of On-Line MPPT Algorithms for PV-Based Battery Storage Systems

    Belqasem Aljafari1, Eydhah Almatrafi2,3,4, Sudhakar Babu Thanikanti5, Sara A. Ibrahim6, Mohamed A. Enany6,*, Marwa M. Ahmed7

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3595-3611, 2022, DOI:10.32604/cmc.2022.030733 - 16 June 2022

    Abstract This paper presents a novel Simulink models with an evaluation study of more widely used On-Line Maximum Power Point tracking (MPPT) techniques for Photo-Voltaic based Battery Storage Systems (PV-BSS). To have a full comparative study in terms of the dynamic response, battery state of charge (SOC), and oscillations around the Maximum Power Point (MPP) of the PV-BSS to variations in climate conditions, these techniques are simulated in Matlab/Simulink. The introduced methodologies are classified into two types; the first type is conventional hill-climbing techniques which are based on instantaneous PV data measurements such as Perturb &… More >

  • Open Access

    ARTICLE

    A Neuro-Fuzzy Approach to Road Traffic Congestion Prediction

    Mohammed Gollapalli1, Atta-ur-Rahman2,*, Dhiaa Musleh2, Nehad Ibrahim2, Muhammad Adnan Khan3, Sagheer Abbas4, Ayesha Atta5, Muhammad Aftab Khan6, Mehwash Farooqui6, Tahir Iqbal7, Mohammed Salih Ahmed6, Mohammed Imran B. Ahmed6, Dakheel Almoqbil8, Majd Nabeel2, Abdullah Omer2

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 295-310, 2022, DOI:10.32604/cmc.2022.027925 - 18 May 2022

    Abstract The fast-paced growth of artificial intelligence applications provides unparalleled opportunities to improve the efficiency of various systems. Such as the transportation sector faces many obstacles following the implementation and integration of different vehicular and environmental aspects worldwide. Traffic congestion is among the major issues in this regard which demands serious attention due to the rapid growth in the number of vehicles on the road. To address this overwhelming problem, in this article, a cloud-based intelligent road traffic congestion prediction model is proposed that is empowered with a hybrid Neuro-Fuzzy approach. The aim of the study… More >

  • Open Access

    ARTICLE

    Secure Dengue Epidemic Prediction System: Healthcare Perspective

    Abdulaziz Aldaej*, Tariq Ahamed Ahanger, Mohammed Yousuf Uddin, Imdad Ullah

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1723-1745, 2022, DOI:10.32604/cmc.2022.027487 - 18 May 2022

    Abstract Viral diseases transmitted by mosquitoes are emerging public health problems across the globe. Dengue is considered to be the most significant mosquito-oriented disease. Conspicuously, the present study provides an effective architecture for Dengue Virus Infection surveillance. The proposed system involves a 4-level architecture for the prediction and prevention of dengue infection outspread. The architectural levels including Dengue Information Acquisition level, Dengue Information Classification level, Dengue-Mining and Extraction level, and Dengue-Prediction and Decision Modeling level enable an individual to periodically monitor his/her probabilistic dengue fever measure. The prediction process is carried out so that proactive measures More >

  • Open Access

    ARTICLE

    Adaptive Neuro-Fuzzy Based Load Frequency Control in Presence of Energy Storage Devices

    Pankaj Jood*, Sanjeev Kumar Aggarwal, Vikram Chopra

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 785-804, 2022, DOI:10.32604/iasc.2022.025217 - 03 May 2022

    Abstract Energy storage technologies are utilized for improving the primary frequency control in complex electrical systems. In this paper, the modeling and simulation of a two-area power system is done to evaluate and compare the impact of three different energy storage applications on load frequency control performance. Capacitive energy storage (CES), battery energy storage (BES), and superconducting magnetic energy storage (SMES) are considered for the study. On the basis of peak overshoot and settling time, the performance of these energy storage devices is compared. The power system consists of thermal, wind, and solar resources. All nonlinearities… More >

  • Open Access

    ARTICLE

    Self-Balancing Vehicle Based on Adaptive Neuro-Fuzzy Inference System

    M. L. Ramamoorthy1, S. Selvaperumal2,*, G. Prabhakar3

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 485-497, 2022, DOI:10.32604/iasc.2022.025824 - 15 April 2022

    Abstract The scope of this research is to design and fuse the sensors used in the self-balancing vehicle through Adaptive Neuro-Fuzzy Inference systems (ANFIS) algorithm to optimize the output. The self-balancing vehicle is a wheeled inverted pendulum, which is extremely complex, nonlinear and unstable. Homogeneous and Heterogeneous sensors are involved in this sensor fusion research to identify the best feasible value among them. The data fusion algorithm present inside the controller of the self-balancing vehicle makes the inputs of the homogeneous sensors and heterogeneous sensors separately for ameliorate surrounding perception. Simulation is performed by modeling the… More >

  • Open Access

    ARTICLE

    Comparative Study of Machine Learning Modeling for Unsteady Aerodynamics

    Mohammad Alkhedher*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1901-1920, 2022, DOI:10.32604/cmc.2022.025334 - 24 February 2022

    Abstract Modern fighters are designed to fly at high angle of attacks reaching 90 deg as part of their routine maneuvers. These maneuvers generate complex nonlinear and unsteady aerodynamic loading. In this study, different aerodynamic prediction tools are investigated to achieve a model which is highly accurate, less computational, and provides a stable prediction of associated unsteady aerodynamics that results from high angle of attack maneuvers. These prediction tools include Artificial Neural Networks (ANN) model, Adaptive Neuro Fuzzy Logic Inference System (ANFIS), Fourier model, and Polynomial Classifier Networks (PCN). The main aim of the prediction model… More >

  • Open Access

    ARTICLE

    A Novel Hybrid MPPT Control Strategy for Isolated Solar PV Power System

    D. Sabaripandiyan1,*, H. Habeebullah Sait2, G. Aarthi3

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1055-1070, 2022, DOI:10.32604/iasc.2022.021950 - 17 November 2021

    Abstract The main aspiration of this paper is to improve the efficiency of Solar Photovoltaic (SPV) power system with a new Hybrid controller for standalone/isolated Solar PV applications is proposed. This controller uses the merits of both Adapted Neuro-Fuzzy Inference System (ANFIS) and Perturbation & Observation (P&O) control techniques to concede rapid recovery at dynamic change of environment conditions such as solar irradiation and temperature. The ANFIS strategy itself has the merits over Fuzzy Logic and ANN methods. Conversely, P&O has its simplicity in implementation. Hence a case study for rapid recovery with the proposed controller… More >

  • Open Access

    ARTICLE

    Software Reliability Assessment Using Hybrid Neuro-Fuzzy Model

    Parul Gandhi1, Mohammad Zubair Khan2, Ravi Kumar Sharma3, Omar H. Alhazmi2, Surbhi Bhatia4,*, Chinmay Chakraborty5

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 891-902, 2022, DOI:10.32604/csse.2022.019943 - 10 November 2021

    Abstract Software reliability is the primary concern of software development organizations, and the exponentially increasing demand for reliable software requires modeling techniques to be developed in the present era. Small unnoticeable drifts in the software can culminate into a disaster. Early removal of these errors helps the organization improve and enhance the software’s reliability and save money, time, and effort. Many soft computing techniques are available to get solutions for critical problems but selecting the appropriate technique is a big challenge. This paper proposed an efficient algorithm that can be used for the prediction of software… More >

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