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  • Open Access


    Numerical Computation of SEIR Model for the Zika Virus Spreading

    Suthep Suantai1,2, Zulqurnain Sabir3,4, Muhammad Asif Zahoor Raja5, Watcharaporn Cholamjiak6,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2155-2170, 2023, DOI:10.32604/cmc.2023.034699

    Abstract The purpose of this study is to present the numerical performances and interpretations of the SEIR nonlinear system based on the Zika virus spreading by using the stochastic neural networks based intelligent computing solver. The epidemic form of the nonlinear system represents the four dynamics of the patients, susceptible patients S(y), exposed patients hospitalized in hospital E(y), infected patients I(y), and recovered patients R(y), i.e., SEIR model. The computing numerical outcomes and performances of the system are examined by using the artificial neural networks (ANNs) and the scaled conjugate gradient (SCG) for the training of the networks, i.e., ANNs-SCG. The… More >

  • Open Access


    Design of a Computational Heuristic to Solve the Nonlinear Liénard Differential Model

    Li Yan1, Zulqurnain Sabir2, Esin Ilhan3, Muhammad Asif Zahoor Raja4, Wei Gao5, Haci Mehmet Baskonus6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 201-221, 2023, DOI:10.32604/cmes.2023.025094

    Abstract In this study, the design of a computational heuristic based on the nonlinear Liénard model is presented using the efficiency of artificial neural networks (ANNs) along with the hybridization procedures of global and local search approaches. The global search genetic algorithm (GA) and local search sequential quadratic programming scheme (SQPS) are implemented to solve the nonlinear Liénard model. An objective function using the differential model and boundary conditions is designed and optimized by the hybrid computing strength of the GA-SQPS. The motivation of the ANN procedures along with GA-SQPS comes to present reliable, feasible and precise frameworks to tackle stiff… More >

  • Open Access


    Fault Recognition of Multilevel Inverter Using Artificial Neural Network Approach

    Aravind Athimoolam1,*, Karthik Balasubramanian2

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1331-1347, 2023, DOI:10.32604/iasc.2023.033465

    Abstract This paper focuses on the development of a diagnostic tool for detecting insulated gate bipolar transistor power electronic switch flaws caused by both open and short circuit faults in multi-level inverter time-frequency output voltage specifications. High-resolution laboratory virtual instrument engineering workbench software testing tool with a sample rate data collection system, as well as specialized signal processing and soft computing technologies, are used in this proposed method. On a single-phase cascaded H-bridge multilevel inverter, simulation and experimental investigations of both open and short issues of the insulated gate bipolar transistor components are performed out. In all conceivable switch issues, the… More >

  • Open Access


    Improving Power Quality by DSTATCOM Based DQ Theory with Soft Computing Techniques

    V. Nandagopal1,*, T. S. Balaji Damodhar2, P. Vijayapriya3, A. Thamilmaran3

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1315-1329, 2023, DOI:10.32604/iasc.2023.032039


    The development of non-linear loads at consumers has significantly impacted power supply systems. Since, the poor power quality has been found in the three-phase distribution system due to unbalanced loads, harmonic current, undesired voltage regulation, and extreme reactive power demand. To overcome this issue, Distributed STATicCOMpensator (DSTATCOM) is implemented. DSTATCOM is a shunt-connected Voltage Source Converter (VSC) that has been utilized in distribution networks to balance the bus voltage in terms of enhancing reactive power control and power factor. DSTATCOM can provide both rapid and continuous capacitive and inductive mode compensation. A rectified resistive and inductive load eliminates current harmonics… More >

  • Open Access


    Review of Optical Character Recognition for Power System Image Based on Artificial Intelligence Algorithm

    Xun Zhang1, Wanrong Bai1, Haoyang Cui2,*

    Energy Engineering, Vol.120, No.3, pp. 665-679, 2023, DOI:10.32604/ee.2023.020342

    Abstract Optical Character Recognition (OCR) refers to a technology that uses image processing technology and character recognition algorithms to identify characters on an image. This paper is a deep study on the recognition effect of OCR based on Artificial Intelligence (AI) algorithms, in which the different AI algorithms for OCR analysis are classified and reviewed. Firstly, the mechanisms and characteristics of artificial neural network-based OCR are summarized. Secondly, this paper explores machine learning-based OCR, and draws the conclusion that the algorithms available for this form of OCR are still in their infancy, with low generalization and fixed recognition errors, albeit with… More >

  • Open Access


    Social Engineering Attack Classifications on Social Media Using Deep Learning

    Yichiet Aun1,*, Ming-Lee Gan1, Nur Haliza Binti Abdul Wahab2, Goh Hock Guan1

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4917-4931, 2023, DOI:10.32604/cmc.2023.032373

    Abstract In defense-in-depth, humans have always been the weakest link in cybersecurity. However, unlike common threats, social engineering poses vulnerabilities not directly quantifiable in penetration testing. Most skilled social engineers trick users into giving up information voluntarily through attacks like phishing and adware. Social Engineering (SE) in social media is structurally similar to regular posts but contains malicious intrinsic meaning within the sentence semantic. In this paper, a novel SE model is trained using a Recurrent Neural Network Long Short Term Memory (RNN-LSTM) to identify well-disguised SE threats in social media posts. We use a custom dataset crawled from hundreds of… More >

  • Open Access


    Resource Exhaustion Attack Detection Scheme for WLAN Using Artificial Neural Network

    Abdallah Elhigazi Abdallah1, Mosab Hamdan2, Shukor Abd Razak3, Fuad A. Ghalib3, Muzaffar Hamzah2,*, Suleman Khan4, Siddiq Ahmed Babikir Ali5, Mutaz H. H. Khairi1, Sayeed Salih6

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5607-5623, 2023, DOI:10.32604/cmc.2023.031047

    Abstract IEEE 802.11 Wi-Fi networks are prone to many denial of service (DoS) attacks due to vulnerabilities at the media access control (MAC) layer of the 802.11 protocol. Due to the data transmission nature of the wireless local area network (WLAN) through radio waves, its communication is exposed to the possibility of being attacked by illegitimate users. Moreover, the security design of the wireless structure is vulnerable to versatile attacks. For example, the attacker can imitate genuine features, rendering classification-based methods inaccurate in differentiating between real and false messages. Although many security standards have been proposed over the last decades to… More >

  • Open Access


    Secured Health Data Transmission Using Lagrange Interpolation and Artificial Neural Network

    S. Vidhya1,*, V. Kalaivani2

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2673-2692, 2023, DOI:10.32604/csse.2023.027724

    Abstract In recent decades, the cloud computing contributes a prominent role in health care sector as the patient health records are transferred and collected using cloud computing services. The doctors have switched to cloud computing as it provides multiple advantageous measures including wide storage space and easy availability without any limitations. This necessitates the medical field to be redesigned by cloud technology to preserve information about patient’s critical diseases, electrocardiogram (ECG) reports, and payment details. The proposed work utilizes a hybrid cloud pattern to share Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) resources over the private and public cloud. The stored… More >

  • Open Access


    A Hybridized Artificial Neural Network for Automated Software Test Oracle

    K. Kamaraj1,*, B. Lanitha2, S. Karthic3, P. N. Senthil Prakash4, R. Mahaveerakannan5

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1837-1850, 2023, DOI:10.32604/csse.2023.029703

    Abstract Software testing is the methodology of analyzing the nature of software to test if it works as anticipated so as to boost its reliability and quality. These two characteristics are very critical in the software applications of present times. When testers want to perform scenario evaluations, test oracles are generally employed in the third phase. Upon test case execution and test outcome generation, it is essential to validate the results so as to establish the software behavior’s correctness. By choosing a feasible technique for the test case optimization and prioritization as along with an appropriate assessment of the application, leads… More >

  • Open Access


    Stochastic Computational Heuristic for the Fractional Biological Model Based on Leptospirosis

    Zulqurnain Sabir1, Sánchez-Chero Manuel2, Muhammad Asif Zahoor Raja3, Gilder-Cieza–Altamirano4, María-Verónica Seminario-Morales2, Fernández Vásquez José Arquímedes5, Purihuamán Leonardo Celso Nazario6, Thongchai Botmart7,*, Wajaree Weera7

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3455-3470, 2023, DOI:10.32604/cmc.2023.033352

    Abstract The purpose of these investigations is to find the numerical outcomes of the fractional kind of biological system based on Leptospirosis by exploiting the strength of artificial neural networks aided by scale conjugate gradient, called ANNs-SCG. The fractional derivatives have been applied to get more reliable performances of the system. The mathematical form of the biological Leptospirosis system is divided into five categories, and the numerical performances of each model class will be provided by using the ANNs-SCG. The exactness of the ANNs-SCG is performed using the comparison of the reference and obtained results. The reference solutions have been obtained… More >

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