Anas W. Abulfaraj^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1137-1156, 2024, DOI:10.32604/cmc.2024.047945

Abstract The utilization of visual attention enhances the performance of image classification tasks. Previous attention-based models have demonstrated notable performance, but many of these models exhibit reduced accuracy when confronted with inter-class and intra-class similarities and differences. Neural-Controlled Differential Equations (N-CDE’s) and Neural Ordinary Differential Equations (NODE’s) are extensively utilized within this context. N-CDE’s possesses the capacity to effectively illustrate both inter-class and intra-class similarities and differences with enhanced clarity. To this end, an attentive neural network has been proposed to generate attention maps, which uses two different types of N-CDE’s, one for adopting hidden layers and the other to generate… More >

Hongsheng Su, Lixia Dong^*, Xiaoying Yu, Kai Liu

Energy Engineering, Vol.121, No.4, pp. 973-986, 2024, DOI:10.32604/ee.2023.043497

Abstract Time based maintenance (TBM) and condition based maintenance (CBM) are widely applied in many large wind farms to optimize the maintenance issues of wind turbine gearboxes, however, these maintenance strategies do not take into account environmental benefits during full life cycle such as carbon emissions issues. Hence, this article proposes a carbon emissions computing model for preventive maintenance activities of wind turbine gearboxes to solve the issue. Based on the change of the gearbox state during operation and the influence of external random factors on the gearbox state, a stochastic differential equation model (SDE) and corresponding carbon emission model are… More > Graphic Abstract

Saima Rashid^1,2,*, Fahd Jarad^3,4

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2289-2327, 2024, DOI:10.32604/cmes.2023.028773

Abstract Because of the features involved with their varied kernels, differential operators relying on convolution formulations have been acknowledged as effective mathematical resources for modeling real-world issues. In this paper, we constructed a stochastic fractional framework of measles spreading mechanisms with dual medication immunization considering the exponential decay and Mittag-Leffler kernels. In this approach, the overall population was separated into five cohorts. Furthermore, the descriptive behavior of the system was investigated, including prerequisites for the positivity of solutions, invariant domain of the solution, presence and stability of equilibrium points, and sensitivity analysis. We included a stochastic element in every cohort and… More >

Sergiy Reutskiy¹, Yuhui Zhang^2,*, Jun Lu^3,*, Ciren Pubu⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1583-1612, 2024, DOI:10.32604/cmes.2023.044878

Abstract This paper presents an efficient numerical technique for solving multi-term linear systems of fractional ordinary differential equations (FODEs) which have been widely used in modeling various phenomena in engineering and science. An approximate solution of the system is sought in the form of the finite series over the Müntz polynomials. By using the collocation procedure in the time interval, one gets the linear algebraic system for the coefficient of the expansion which can be easily solved numerically by a standard procedure. This technique also serves as the basis for solving the time-fractional partial differential equations (PDEs). The modified radial basis… More >

Rania Saadah¹, Mohammed Amleh¹, Ahmad Qazza¹, Shrideh Al-Omari^2,*, Ahmet Ocak Akdemir³

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1593-1616, 2024, DOI:10.32604/cmes.2023.029180

Abstract In this study, we aim to investigate certain triple integral transform and its application to a class of partial differential equations. We discuss various properties of the new transform including inversion, linearity, existence, scaling and shifting, etc. Then, we derive several results enfolding partial derivatives and establish a multi-convolution theorem. Further, we apply the aforementioned transform to some classical functions and many types of partial differential equations involving heat equations, wave equations, Laplace equations, and Poisson equations as well. Moreover, we draw some figures to illustrate 3-D contour plots for exact solutions of some selected examples involving different values in… More >

Jiepeng Yao^1,2, Zhanjia Peng^1,2, Jingjing Liu^1,2, Chengxiao Fan^1,2, Zhongyi Wang^1,2,3, Lan Huang^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2243-2265, 2023, DOI:10.32604/cmes.2023.028101

Abstract In the establishment of differential equations, the determination of time-varying parameters is a difficult problem, especially for equations related to life activities. Thus, we propose a new framework named BioE-PINN based on a physical information neural network that successfully obtains the time-varying parameters of differential equations. In the proposed framework, the learnable factors and scale parameters are used to implement adaptive activation functions, and hard constraints and loss function weights are skillfully added to the neural network output to speed up the training convergence and improve the accuracy of physical information neural networks. In this paper, taking the electrophysiological differential… More >

Yu-Ming Chu¹, Sobia Sultana², Saima Rashid^3,*, Mohammed Shaaf Alharthi⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2427-2464, 2023, DOI:10.32604/cmes.2023.028771

Abstract Various data sets showing the prevalence of numerous viral diseases have demonstrated that the transmission is not truly homogeneous. Two examples are the spread of Spanish flu and COVID-19. The aim of this research is to develop a comprehensive nonlinear stochastic model having six cohorts relying on ordinary differential equations via piecewise fractional differential operators. Firstly, the strength number of the deterministic case is carried out. Then, for the stochastic model, we show that there is a critical number that can predict virus persistence and infection eradication. Because of the peculiarity of this notion, an interesting way… More >

T. M. Agbaje^a,b, S. S. Motsa^a,* , S. Mondal^c,† , P. Sibanda^a

Frontiers in Heat and Mass Transfer, Vol.9, pp. 1-13, 2017, DOI:10.5098/hmt.9.36

Abstract In this work, we present a compliment of the spectral perturbation method (SPM) for solving nonlinear partial differential equations (PDEs) with applications in fluid flow problems. The (SPM) is a series expansion based approach that uses the Chebyshev spectral collocation method to solve the governing sequence of differential equation generated by the perturbation series approximation. Previously the SPM had the limitation of being used to solve problems with small parameters only. This current investigation seeks to improve the performance of the SPM by doing the series expansion about a large parameter. The new method namely the large parameter spectral perturbation… More >

Augusto González Bonorino^1,*, Malick Ndiaye², Casimer DeCusatis²

Journal of Quantum Computing, Vol.4, No.3, pp. 135-146, 2022, DOI:10.32604/jqc.2022.036706

Abstract The well-known Riccati differential equations play a key role in many fields, including problems in protein folding, control and stabilization, stochastic control, and cybersecurity (risk analysis and malware propagation). Quantum computer algorithms have the potential to implement faster approximate solutions to the Riccati equations compared with strictly classical algorithms. While systems with many qubits are still under development, there is significant interest in developing algorithms for near-term quantum computers to determine their accuracy and limitations. In this paper, we propose a hybrid quantum-classical algorithm, the Matrix Riccati Solver (MRS). This approach uses a transformation of variables to turn a set… More >

V.S. Sampath Kumar, N.P. Pai^† , B. Devaki

Frontiers in Heat and Mass Transfer, Vol.20, pp. 1-13, 2023, DOI:10.5098/hmt.20.30

Abstract In the present study, we consider Casson fluid flow between two porous plates with permeability criteria in the presence of heat transfer and magnetic effect. A proper set of similarity transformations simplify the Navier-Stokes equations to non-linear ODEs with boundary conditions. The homotopy perturbation method is an efficient and stable method which is used to get solutions. Further, the results obtained are compared with the solution computed through an effective and efficient finite difference approach. The purpose of this analysis is to study the four different cases arise viz: suction, injection, mixed suction and mixed injection in this problem, along… More >