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  • Open Access

    ARTICLE

    A Power Battery Fault Diagnosis Method Based on Long-Short Term Memory-Back Propagation

    Yuheng Yin, Jiahao Song*, Minghui Yang

    Energy Engineering, Vol.122, No.2, pp. 709-731, 2025, DOI:10.32604/ee.2024.059021 - 31 January 2025

    Abstract The lithium battery is an essential component of electric cars; prompt and accurate problem detection is vital in guaranteeing electric cars’ safe and dependable functioning and addressing the limitations of Back Propagation (BP) neural networks in terms of vanishing gradients and inability to effectively capture dependencies in time series, and the limitations of Long-Short Term Memory (LSTM) neural network models in terms of risk of overfitting. A method based on LSTM-BP is put forward for power battery fault diagnosis to improve the accuracy of lithium battery fault diagnosis. First, a lithium battery model is constructed… More >

  • Open Access

    ARTICLE

    XGBoost Based Multiclass NLOS Channels Identification in UWB Indoor Positioning System

    Ammar Fahem Majeed1,2,*, Rashidah Arsat1, Muhammad Ariff Baharudin1, Nurul Mu’azzah Abdul Latiff1, Abbas Albaidhani3

    Computer Systems Science and Engineering, Vol.49, pp. 159-183, 2025, DOI:10.32604/csse.2024.058741 - 03 January 2025

    Abstract Accurate non-line of sight (NLOS) identification technique in ultra-wideband (UWB) location-based services is critical for applications like drone communication and autonomous navigation. However, current methods using binary classification (LOS/NLOS) oversimplify real-world complexities, with limited generalisation and adaptability to varying indoor environments, thereby reducing the accuracy of positioning. This study proposes an extreme gradient boosting (XGBoost) model to identify multi-class NLOS conditions. We optimise the model using grid search and genetic algorithms. Initially, the grid search approach is used to identify the most favourable values for integer hyperparameters. In order to achieve an optimised model configuration,… More >

  • Open Access

    ARTICLE

    Novel Methodologies for Preventing Crack Propagation in Steel Gas Pipelines Considering the Temperature Effect

    Nurlan Zhangabay1,*, Ulzhan Ibraimova2, Marco Bonopera3,*, Ulanbator Suleimenov1, Konstantin Avramov4, Maryna Chernobryvko4, Aigerim Yessengali1

    Structural Durability & Health Monitoring, Vol.19, No.1, pp. 1-23, 2025, DOI:10.32604/sdhm.2024.053391 - 15 November 2024

    Abstract Using the software ANSYS-19.2/Explicit Dynamics, this study performed finite-element modeling of the large-diameter steel pipeline cross-section for the Beineu-Bozoy-Shymkent gas pipeline with a non-through straight crack, strengthened by steel wire wrapping. The effects of the thread tensile force of the steel winding in the form of single rings at the crack edges and the wires with different winding diameters and pitches were also studied. The results showed that the strengthening was preferably executed at a minimum value of the thread tensile force, which was 6.4% more effective than that at its maximum value. The analysis… More >

  • Open Access

    ARTICLE

    Orthogonal Probability Approximation for Highly Accurate and Efficient Orbit Uncertainty Propagation

    Pugazhenthi Sivasankar1,*, Austin B. Probe2, Tarek A. Elgohary1

    Digital Engineering and Digital Twin, Vol.2, pp. 169-205, 2024, DOI:10.32604/dedt.2024.052805 - 31 December 2024

    Abstract In Space Situational Awareness (SSA), accurate and efficient uncertainty quantification and propagation are essential for various applications, such as conjunction analysis, track correlation, and orbit prediction. The propagation of the probability density function (PDF) in nonlinear systems results in non-Gaussian distributions, which are difficult to approximate. Furthermore, the computational cost of approximating the PDF increases exponentially with the number of random variables, a phenomenon known as the curse of dimensionality. To address these challenges, the Orthogonal Probability Approximation (OPA) method is presented for high-fidelity uncertainty propagation and PDF approximation in nonlinear dynamical systems. The method… More >

  • Open Access

    ARTICLE

    Research on Substation Siting Based on a 3D GIS Platform and an Improved BP Neural Network

    Yao Jin1,2,*, Jie Zhao1,2, Xiaozhe Tan1,2, Linghou Miao1,2, Wenxing Yu1,2

    Digital Engineering and Digital Twin, Vol.2, pp. 131-144, 2024, DOI:10.32604/dedt.2024.048142 - 31 December 2024

    Abstract Substation siting is an important foundation and a key task in power system planning. The article is based on a three-dimensional GIS platform combined with an improved BP neural network algorithm and proposes a substation siting method that is more efficient, accurate and provides a better user experience. Firstly, the BP algorithm is enhanced to improve its convergence speed and computational efficiency for a more accurate and reasonable calculation of optimal site selection. Then, a 24-item selection index system with 7 categories is proposed, which provides quantifiable data support and an evaluation basis for substation… More >

  • Open Access

    ARTICLE

    Employing a Backpropagation Neural Network for Predicting Fear of Cancer Recurrence among Non-Small Cell Lung Cancer Patients

    Man Liu1, Zhuoheng Lv1,#, Hongjing Wang2,*, Lu Liu1,*

    Psycho-Oncologie, Vol.18, No.4, pp. 305-316, 2024, DOI:10.32604/po.2024.054098 - 04 December 2024

    Abstract Objective: Non-small cell lung cancer (NSCLC) patients often experience significant fear of recurrence. To facilitate precise identification and appropriate management of this fear, this study aimed to compare the efficacy and accuracy of a Backpropagation Neural Network (BPNN) against logistic regression in modeling fear of cancer recurrence prediction. Methods: Data from 596 NSCLC patients, collected between September 2023 and December 2023 at the Cancer Hospital of the Chinese Academy of Medical Sciences, were analyzed. Nine clinically and statistically significant variables, identified via univariate logistic regression, were inputted into both BPNN and logistic regression models developed… More >

  • Open Access

    PROCEEDINGS

    Numerical Modeling for Crack Propagation Based on a Multifunctional Super Singular Element

    Xuecheng Ping1,2,*, Congman Wang1,2, Xingxing Wang1,2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.011724

    Abstract The traditional finite element method (FEM) often requires a large number of refined meshes to analyze the mechanical behavior of geometric discontinuities, its computational efficiency and convergence speed are affected. A FEM for crack propagation based on the combination of an adaptive remeshing technique with the multifunctional super singular element (MSSE) at the crack tip is proposed for the fracture process simulation of two-dimensional (2D) materials. The adaptive FEM for crack propagation divides the crack tip neighborhood into the MSSE region, the protection element (PE) region and the background element (BE) region. The MSSE is… More >

  • Open Access

    PROCEEDINGS

    Characterization and Numerical Simulation of Delamination Propagation Behavior in Carbon Fiber Reinforced Composite Laminates

    Yu Gong1,*, Jianyu Zhang1, Libin Zhao2, Ning Hu2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.011451

    Abstract Advanced carbon fiber reinforced composite materials are increasingly being used in aerospace and other fields. Composite laminate structure is one of the commonly used configurations, but due to weak interlayer performance, interlayer delamination is prone to occur [1]. The occurrence and growth of delamination will seriously affect the overall integrity and safety of composite structures, making it a focus of attention in the design of laminated structures. Accurately characterizing the delamination mechanical properties of composite laminates and simulating delamination propagation behavior is the basis for damage tolerance design and analysis of composite structures with delamination… More >

  • Open Access

    PROCEEDINGS

    Crack Dynamics Propagation in the Fractured Geothermal Reservoir Under Thermo-Hydro-Mechanical-Chemical Coupling

    Weitao Zhang1, Dongxu Han2,*, Yujie Chen2, Tingyu Li3, Liang Gong1,*, Bo Yu2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-2, 2024, DOI:10.32604/icces.2024.011484

    Abstract As climate change accelerates due to fossil fuel use, geothermal energy emerges as an indispensable renewable solution 1. Hot dry rock (HDR) reservoirs, accounting for more than 90% of total geothermal resources 2, have gained wide attention worldwide for their abundant reserves, wide distribution, and carbon-free, stable, and efficient supply characteristics 3. While HDR geothermal energy offers significant potential, its development faces challenges, including the complex interaction between fluid flow, heat transfer, reactive solute transport, and the rock’s mechanical processes, referred to as the THMC coupling process 4. Cracks, ubiquitous in HDR geothermal reservoirs, exhibit… More >

  • Open Access

    ARTICLE

    Virtual Assembly Collision Detection Algorithm Using Backpropagation Neural Network

    Baowei Wang1,2,*, Wen You2

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1085-1100, 2024, DOI:10.32604/cmc.2024.055538 - 15 October 2024

    Abstract As computer graphics technology continues to advance, Collision Detection (CD) has emerged as a critical element in fields such as virtual reality, computer graphics, and interactive simulations. CD is indispensable for ensuring the fidelity of physical interactions and the realism of virtual environments, particularly within complex scenarios like virtual assembly, where both high precision and real-time responsiveness are imperative. Despite ongoing developments, current CD techniques often fall short in meeting these stringent requirements, resulting in inefficiencies and inaccuracies that impede the overall performance of virtual assembly systems. To address these limitations, this study introduces a… More >

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