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Search Results (18)
  • Open Access


    Fractional Order Environmental and Economic Model Investigations Using Artificial Neural Network

    Wajaree Weera1, Chantapish Zamart1, Zulqurnain Sabir2,3, Muhammad Asif Zahoor Raja4, Afaf S. Alwabli5, S. R. Mahmoud6, Supreecha Wongaree7, Thongchai Botmart1,*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1735-1748, 2023, DOI:10.32604/cmc.2023.032950

    Abstract The motive of these investigations is to provide the importance and significance of the fractional order (FO) derivatives in the nonlinear environmental and economic (NEE) model, i.e., FO-NEE model. The dynamics of the NEE model achieves more precise by using the form of the FO derivative. The investigations through the non-integer and nonlinear mathematical form to define the FO-NEE model are also provided in this study. The composition of the FO-NEE model is classified into three classes, execution cost of control, system competence of industrial elements and a new diagnostics technical exclusion cost. The mathematical… More >

  • Open Access


    A Stochastic Study of the Fractional Order Model of Waste Plastic in Oceans

    Muneerah Al Nuwairan1,*, Zulqurnain Sabir2, Muhammad Asif Zahoor Raja3, Maryam Alnami1, Hanan Almuslem1

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4441-4454, 2022, DOI:10.32604/cmc.2022.029432

    Abstract In this paper, a fractional order model based on the management of waste plastic in the ocean (FO-MWPO) is numerically investigated. The mathematical form of the FO-MWPO model is categorized into three components, waste plastic, Marine debris, and recycling. The stochastic numerical solvers using the Levenberg-Marquardt backpropagation neural networks (LMQBP-NNs) have been applied to present the numerical solutions of the FO-MWPO system. The competency of the method is tested by taking three variants of the FO-MWPO model based on the fractional order derivatives. The data ratio is provided for training, testing and authorization is 77%, More >

  • Open Access


    A Novel Stochastic Framework for the MHD Generator in Ocean

    Sakda Noinang1, Zulqurnain Sabir2, Shumaila Javeed3, Muhammad Asif Zahoor Raja4, Dostdar Ali3, Wajaree Weera5,*, Thongchai Botmart5

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3383-3402, 2022, DOI:10.32604/cmc.2022.029166

    Abstract This work aims to study the nonlinear ordinary differential equations (ODEs) system of magnetohydrodynamic (MHD) past over an inclined plate using Levenberg-Marquardt backpropagation neural networks (LMBNNs). The stochastic procedures LMBNNs are provided with three categories of sample statistics, testing, training, and verification. The nonlinear MHD system past over an inclined plate is divided into three profiles, dimensionless momentum, species (salinity), and energy (heat) conservations. The data is applied 15%, 10%, and 75% for validation, testing, and training to solve the nonlinear system of MHD past over an inclined plate. A reference data set is designed More >

  • Open Access


    Dynamics of Fractional Differential Model for Schistosomiasis Disease

    Thongchai Botmart1, Wajaree Weera1,*, Muhammad Asif Zahoor Raja2, Zulqurnain Sabir3, Qusain Hiader4, Gilder Cieza Altamirano5, Plinio Junior Muro Solano6, Alfonso Tesen Arroyo6

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 981-999, 2022, DOI:10.32604/cmc.2022.028921

    Abstract In the present study, a design of a fractional order mathematical model is presented based on the schistosomiasis disease. To observe more accurate performances of the results, the use of fractional order derivatives in the mathematical model is introduce based on the schistosomiasis disease is executed. The preliminary design of the fractional order mathematical model focused on schistosomiasis disease is classified as follows: uninfected with schistosomiasis, infected with schistosomiasis, recovered from infection, susceptible snail unafflicted with schistosomiasis disease and susceptible snail afflicted with this disease. The solutions to the proposed system of the fractional order… More >

  • Open Access


    Novel Computing for the Delay Differential Two-Prey and One-Predator System

    Prem Junsawang1, Zulqurnain Sabir2, Muhammad Asif Zahoor Raja3, Soheil Salahshour4, Thongchai Botmart5,*, Wajaree Weera3

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 249-263, 2022, DOI:10.32604/cmc.2022.028513

    Abstract The aim of these investigations is to find the numerical performances of the delay differential two-prey and one-predator system. The delay differential models are very significant and always difficult to solve the dynamical kind of ecological nonlinear two-prey and one-predator system. Therefore, a stochastic numerical paradigm based artificial neural network (ANN) along with the Levenberg-Marquardt backpropagation (L-MB) neural networks (NNs), i.e., L-MBNNs is proposed to solve the dynamical two-prey and one-predator model. Three different cases based on the dynamical two-prey and one-predator system have been discussed to check the correctness of the L-MBNNs. The statistic More >

  • Open Access


    Intelligent Networks for Chaotic Fractional-Order Nonlinear Financial Model

    Prem Junswang1, Zulqurnain Sabir2, Muhammad Asif Zahoor Raja3, Waleed Adel4,5, Thongchai Botmart6,*, Wajaree Weera6

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5015-5030, 2022, DOI:10.32604/cmc.2022.027523

    Abstract The purpose of this paper is to present a numerical approach based on the artificial neural networks (ANNs) for solving a novel fractional chaotic financial model that represents the effect of memory and chaos in the presented system. The method is constructed with the combination of the ANNs along with the Levenberg-Marquardt backpropagation (LMB), named the ANNs-LMB. This technique is tested for solving the novel problem for three cases of the fractional-order values and the obtained results are compared with the reference solution. Fifteen numbers neurons have been used to solve the fractional-order chaotic financial More >

  • Open Access


    Nonlinear Dynamics of Nervous Stomach Model Using Supervised Neural Networks

    Zulqurnain Sabir1, Manoj Gupta2, Muhammad Asif Zahoor Raja3, N. Seshagiri Rao4, Muhammad Mubashar Hussain5, Faisal Alanazi6, Orawit Thinnukool7, Pattaraporn Khuwuthyakorn7,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1627-1644, 2022, DOI:10.32604/cmc.2022.021462

    Abstract The purpose of the current investigations is to solve the nonlinear dynamics based on the nervous stomach model (NSM) using the supervised neural networks (SNNs) along with the novel features of Levenberg-Marquardt backpropagation technique (LMBT), i.e., SNNs-LMBT. The SNNs-LMBT is implemented with three different types of sample data, authentication, testing and training. The ratios for these statistics to solve three different variants of the nonlinear dynamics of the NSM are designated 75% for training, 15% for validation and 10% for testing, respectively. For the numerical measures of the nonlinear dynamics of the NSM, the Runge-Kutta More >

  • Open Access


    Inverse Analysis of Origin-Destination matrix for Microscopic Traffic Simulator

    K. Abe1, H. Fujii1, S. Yoshimura1

    CMES-Computer Modeling in Engineering & Sciences, Vol.113, No.1, pp. 71-87, 2017, DOI:10.3970/cmes.2017.113.068

    Abstract Microscopic traffic simulations are useful for solving various traffic- related problems, e.g. traffic jams and accidents, local and global environmental and energy problems, maintaining mobility in aging societies, and evacuation plan- ning for natural as well as man-made disasters. The origin-destination (OD) matrix is often used as the input to represent traffic demands into traffic simulators. In this study, we propose an indirect method for estimating the OD matrix using a traffic simulator as an internal model. The proposed method is designed to output results that are consistent with the input of the simulator. The More >

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