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  • Open Access

    ARTICLE

    Estimating Fuel-Efficient Air Plane Trajectories Using Machine Learning

    Jaiteg Singh1, Gaurav Goyal1, Farman Ali2, Babar Shah3, Sangheon Pack4,*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6189-6204, 2022, DOI:10.32604/cmc.2022.021657 - 11 October 2021

    Abstract Airline industry has witnessed a tremendous growth in the recent past. Percentage of people choosing air travel as first choice to commute is continuously increasing. Highly demanding and congested air routes are resulting in inadvertent delays, additional fuel consumption and high emission of greenhouse gases. Trajectory planning involves creation identification of cost-effective flight plans for optimal utilization of fuel and time. This situation warrants the need of an intelligent system for dynamic planning of optimized flight trajectories with least human intervention required. In this paper, an algorithm for dynamic planning of optimized flight trajectories has… More >

  • Open Access

    ARTICLE

    Numerical Simulations for Stochastic Computer Virus Propagation Model

    Muhammad Shoaib Arif1, *, Ali Raza1, Muhammad Rafiq2, Mairaj Bibi3, Javeria Nawaz Abbasi3, Amna Nazeer3, Umer Javed4

    CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 61-77, 2020, DOI:10.32604/cmc.2020.08595

    Abstract We are presenting the numerical simulations for the stochastic computer virus propagation model in this manuscript. We are comparing the solutions of stochastic and deterministic computer virus models. Outcomes of a threshold number R0 hold in stochastic computer virus model. If R0 < 1 then in such a condition virus controlled in the computer population while R0 > 1 shows virus rapidly spread in the computer population. Unfortunately, stochastic numerical techniques fail to cope with large step sizes of time. The suggested structure of the stochastic non-standard finite difference technique can never violate the dynamical properties. On More >

  • Open Access

    ARTICLE

    Galerkin Solution of Stochastic Beam Bending on Winkler Foundations

    C. R. A. Silva1, H. P. Azikri de Deus1, G.E. Mantovani2, A.T. Beck3

    CMES-Computer Modeling in Engineering & Sciences, Vol.67, No.2, pp. 119-150, 2010, DOI:10.3970/cmes.2010.067.119

    Abstract In this paper, the Askey-Wiener scheme and the Galerkin method are used to obtain approximate solutions to stochastic beam bending on Winkler foundation. The study addresses Euler-Bernoulli beams with uncertainty in the bending stiffness modulus and in the stiffness of the foundation. Uncertainties are represented by parameterized stochastic processes. The random behavior of beam response is modeled using the Askey-Wiener scheme. One contribution of the paper is a sketch of proof of existence and uniqueness of the solution to problems involving fourth order operators applied to random fields. From the approximate Galerkin solution, expected value More >

  • Open Access

    ARTICLE

    A Stochastic Analysis of a Brownian Ratchet Model for Actin-Based Motility

    Hong Qian1

    Molecular & Cellular Biomechanics, Vol.1, No.4, pp. 267-278, 2004, DOI:10.3970/mcb.2004.001.267

    Abstract In recent single-particle tracking (SPT) measurements on Listeria monocytogenes motility in cells [Kuo and McGrath (2000)], the actin-based stochastic dynamics of the bacterium movement has been analyzed statistically in terms of the mean-square displacement (MSD) of the trajectory. We present a stochastic analysis of a simplified polymerization Brownian ratchet (BR) model in which motions are limited by the bacterium movement. Analytical results are obtained and statistical data analyses are investigated. It is shown that the MSD of the stochastic bacterium movement is a monotonic quadratic function while the MSD for detrended trajectories is linear. Both the More >

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