Xiaoyi Wang¹, Xinyue Chang², Wenxuan Wang^1,*, Zijie Qiao³, Feng Zhang^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1775-1796, 2024, DOI:10.32604/cmes.2023.043913 - 29 January 2024

Abstract The objective of reliability-based design optimization (RBDO) is to minimize the optimization objective while satisfying the corresponding reliability requirements. However, the nested loop characteristic reduces the efficiency of RBDO algorithm, which hinders their application to high-dimensional engineering problems. To address these issues, this paper proposes an efficient decoupled RBDO method combining high dimensional model representation (HDMR) and the weight-point estimation method (WPEM). First, we decouple the RBDO model using HDMR and WPEM. Second, Lagrange interpolation is used to approximate a univariate function. Finally, based on the results of the first two steps, the original nested More >

Xiang Li¹, Guangyan Huang^1,2,*, Zhiwei Guo^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-3, 2023, DOI:10.32604/icces.2023.09269

Abstract SPH method is widely used to study the dynamic response of metal casing under explosive loading because of its superiority in simulating metal fracture phenomenon [1-3]. The distribution of the fragment from uncoupled charge structures with segmental shaped explosive were studied. The X-ray photographic images of fragmentation obtained from explosion experiment were compared with the numerical results based on SPH method and Lagrange method. The fragmentation shows that the numerical results based on the Lagrange method are in good agreement with the experimental results while some errors appear in results based on SPH method. The More >

S. Vidhya^1,*, V. Kalaivani²

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2673-2692, 2023, DOI:10.32604/csse.2023.027724 - 21 December 2022

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… More >

Ying Li¹, Longxiang Xu¹, Fangjun Mei¹, Shihui Ying^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 657-672, 2023, DOI:10.32604/cmes.2022.021277 - 24 August 2022

Abstract We propose new hybrid Lagrange neural networks called LaNets to predict the numerical solutions of partial differential equations. That is, we embed Lagrange interpolation and small sample learning into deep neural network frameworks. Concretely, we first perform Lagrange interpolation in front of the deep feedforward neural network. The Lagrange basis function has a neat structure and a strong expression ability, which is suitable to be a preprocessing tool for pre-fitting and feature extraction. Second, we introduce small sample learning into training, which is beneficial to guide the model to be corrected quickly. Taking advantages of More >

C. K. Morarji^1,*, N. Sathish Kumar²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2875-2892, 2023, DOI:10.32604/iasc.2023.025776 - 17 August 2022

Abstract One of the recent advancements in the electrical power systems is the smart-grid technology. For the effective functioning of the smart grid, the process like monitoring and controlling have to be given importance. In this paper, the Wireless Sensor Network (WSN) is utilized for tracking the power in smart grid applications. The smart grid is used to produce the electricity and it is connected with the sensor to transmit or receive the data. The data is transmitted quickly by using the Probabilistic Neural Network (PNN), which aids in identifying the shortest path of the nodes. More >

Amr M. S. Mahdy^1,*, Mohamed S. Mohamed¹, Ahoud Y. Al Amiri², Khaled A. Gepreel¹

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 899-915, 2022, DOI:10.32604/iasc.2022.017801 - 22 September 2021

Abstract In this manuscript, we solve the ordinary model of nonlinear smoking mathematically by using the second kind of shifted Chebyshev polynomials. The stability of the equilibrium point is calculated. The schematic of the model illustrates our proposition. We discuss the optimal control of this model, and formularize the optimal control smoking work through the necessary optimality cases. A numerical technique for the simulation of the control problem is adopted. Moreover, a numerical method is presented, and its stability analysis discussed. Numerical simulation then demonstrates our idea. Optimal control for the model is further discussed by More >

Zihao Zong, Tielin Shi, Qi Xia^*

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 283-295, 2021, DOI:10.32604/cmes.2021.015975 - 28 June 2021

Abstract A parameter-free approach is proposed to determine the Lagrange multiplier for the constraint of material volume in the level set method. It is inspired by the procedure of determining the threshold of sensitivity number in the BESO method. It first computes the difference between the volume of current design and the upper bound of volume. Then, the Lagrange multiplier is regarded as the threshold of sensitivity number to remove the redundant material. Numerical examples proved that this approach is effective to constrain the volume. More importantly, there is no parameter in the proposed approach, which More >

Miaomiao Yang, Wentao Ma, Yongbin Ge^*

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.1, pp. 25-54, 2021, DOI:10.32604/cmes.2021.012575 - 22 December 2020

Abstract In this paper, Chebyshev interpolation nodes and barycentric Lagrange interpolation basis function are used to deduce the scheme for solving the Helmholtz equation. First of all, the interpolation basis function is applied to treat the spatial variables and their partial derivatives, and the collocation method for solving the second order differential equations is established. Secondly, the differential equations on a given test node. Finally, based on three kinds of test nodes, numerical experiments show that the present scheme can not only calculate the high wave numbers problems, but also calculate the variable wave numbers problems. More >

Mushtaq Ahmad Khan^1,*, Ahmed B. Altamimi², Zawar Hussain Khan³, Khurram Shehzad Khattak³, Sahib Khan^4,*, Asmat Ullah³, Murtaza Ali¹

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.1, pp. 55-88, 2021, DOI:10.32604/cmes.2021.011163 - 22 December 2020

Abstract This article introduces a fast meshless algorithm for the numerical solution nonlinear partial differential equations (PDE) by Radial Basis Functions (RBFs) approximation connected with the Total Variation (TV)-based minimization functional and to show its application to image denoising containing multiplicative noise. These capabilities used within the proposed algorithm have not only the quality of image denoising, edge preservation but also the property of minimization of staircase effect which results in blocky effects in the images. It is worth mentioning that the recommended method can be easily employed for nonlinear problems due to the lack of More >

Dumitru Baleanu^1,2, Behzad Ghanbari³, Jihad H. Asad^4,*, Amin Jajarmi⁵, Hassan Mohammadi Pirouz⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 953-968, 2020, DOI:10.32604/cmes.2020.010236 - 21 August 2020

Abstract In this work, a system of three masses on the vertices of equilateral triangle is investigated. This system is known in the literature as a planar system. We first give a description to the system by constructing its classical Lagrangian. Secondly, the classical Euler-Lagrange equations (i.e., the classical equations of motion) are derived. Thirdly, we fractionalize the classical Lagrangian of the system, and as a result, we obtain the fractional Euler-Lagrange equations. As the final step, we give the numerical simulations of the fractional model, a new model which is based on Caputo fractional derivative. More >