Tiankui Sun^*, Shuyi Zhuang, Yongling Lu, Wenqiang Xie, Ning Guo, Sudi Xu

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.070213 - 27 December 2025

Abstract To ensure an uninterrupted power supply, mobile power sources (MPS) are widely deployed in power grids during emergencies. Comprising mobile emergency generators (MEGs) and mobile energy storage systems (MESS), MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies, offering advantages such as flexibility and high resilience through electricity delivery via transportation networks. This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator (DWIG) intended for MEG applications, employing an improved particle swarm optimization (PSO) algorithm based on a back-propagation neural network (BPNN). A… More >

Lijie Wang¹, Xuguang Dong¹, Yao Lu¹, Xiaoming Du^1,*, Jide Liu²

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3787-3803, 2025, DOI:10.32604/cmc.2025.070696 - 23 September 2025

Abstract The available datasets provided by our previous works on creep life for nickel-based single crystal superalloys were analyzed through supervised machine learning to rank features in terms of their importance for determining creep life. We employed six models, namely Back Propagation Neural Network (BPNN), Gradient Boosting Decision Tree (GBDT), Random Forest (RF), Gaussian Process Regression (GPR), XGBoost, and CatBoost, to predict the creep life. Our investigation showed that the BPNN model with a network structure of “24-7(20)-1” (which consists of 24 input layers, 7 hidden layers, 20 neurons, and 1 output layer) performed better than More >

Borui Wang, Dongyue Gao^*, Haiyang Gu, Mengke Ding, Zhanjun Wu

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 455-473, 2025, DOI:10.32604/cmc.2025.060617 - 26 March 2025

Abstract Fatigue damage is a primary contributor to the failure of composite structures, underscoring the critical importance of monitoring its progression to ensure structural safety. This paper introduces an innovative approach to fatigue damage monitoring in composite structures, leveraging a hybrid methodology that integrates the Whale Optimization Algorithm (WOA)-Backpropagation (BP) neural network with an ultrasonic guided wave feature selection algorithm. Initially, a network of piezoelectric ceramic sensors is employed to transmit and capture ultrasonic-guided waves, thereby establishing a signal space that correlates with the structural condition. Subsequently, the Relief-F algorithm is applied for signal feature extraction,… More >

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 > Graphic Abstract

Yao Jin^1,2,*, Jie Zhao^1,2, Xiaozhe Tan^1,2, Linghou Miao^1,2, Wenxing Yu^1,2

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 >

Qi Zhuang^1,*, Dong Liu², Zhuo Chen³

Energy Engineering, Vol.121, No.3, pp. 821-834, 2024, DOI:10.32604/ee.2023.044054 - 27 February 2024

Abstract Oil and gas pipelines are affected by many factors, such as pipe wall thinning and pipeline rupture. Accurate prediction of failure pressure of oil and gas pipelines can provide technical support for pipeline safety management. Aiming at the shortcomings of the BP Neural Network (BPNN) model, such as low learning efficiency, sensitivity to initial weights, and easy falling into a local optimal state, an Improved Sparrow Search Algorithm (ISSA) is adopted to optimize the initial weights and thresholds of BPNN, and an ISSA-BPNN failure pressure prediction model for corroded pipelines is established. Taking 61 sets More >

Guilin Wu^1,2, Shenghua Huang¹, Tingting Liu³, Zhuoni Yang³, Yuesong Wu², Guihong Wei¹, Peng Yu^1,*, Qilin Zhang⁴, Jun Feng⁴, Bo Zeng^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2709-2725, 2024, DOI:10.32604/cmes.2023.031399 - 15 December 2023

Abstract Esophageal disease is a common disorder of the digestive system that can severely affect the quality of life and prognosis of patients. Esophageal stenting is an effective treatment that has been widely used in clinical practice. However, esophageal stents of different types and parameters have varying adaptability and effectiveness for patients, and they need to be individually selected according to the patient’s specific situation. The purpose of this study was to provide a reference for clinical doctors to choose suitable esophageal stents. We used 3D printing technology to fabricate esophageal stents with different ratios of… More >

Jiang Li, Jiutao Zhao, Qinhui Liu^*, Laizheng Zhu, Jinyi Guo, Weijiu Zhang

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 223-244, 2023, DOI:10.32604/cmc.2023.042429 - 31 October 2023

Abstract Cutting parameters have a significant impact on the machining effect. In order to reduce the machining time and improve the machining quality, this paper proposes an optimization algorithm based on Bp neural network-Improved Multi-Objective Particle Swarm (Bp-DWMOPSO). Firstly, this paper analyzes the existing problems in the traditional multi-objective particle swarm algorithm. Secondly, the Bp neural network model and the dynamic weight multi-objective particle swarm algorithm model are established. Finally, the Bp-DWMOPSO algorithm is designed based on the established models. In order to verify the effectiveness of the algorithm, this paper obtains the required data through More >

Deng Lu¹, Xujun Lang¹, Bo Yang¹, Ziyang Li¹, Hang Geng^2,*

Energy Engineering, Vol.120, No.10, pp. 2287-2306, 2023, DOI:10.32604/ee.2023.029140 - 28 September 2023

Abstract The four-circuit parallel line on the same tower effectively solves the problems faced by the line reconstruction and construction under the condition of the increasing shortage of transmission corridors. Optimizing the conductor and phase sequence arrangement of multiple transmission lines is conducive to improving electromagnetic and electrostatic coupling caused by electromagnetic problems. This paper uses the ATP-EMTP simulation software to build a 500 kV multi-circuit transmission line on the same tower. It stimulates the induced voltage and current values of different line lengths, tower spacing, vertical and horizontal spacing between different circuits, phase sequence arrangement,… More >

Shuiping Zhang^1,2, Xi Liang³, Lin Shi², Lei Yan⁴, Jun Tang^1,2,*

Sound & Vibration, Vol.57, pp. 29-44, 2023, DOI:10.32604/sv.2023.041350 - 07 September 2023

Abstract The filter-x least mean square (FxLMS) algorithm is widely used in active noise control (ANC) systems. However, because the algorithm is a feedback control algorithm based on the minimization of the error signal variance to update the filter coefficients, it has a certain delay, usually has a slow convergence speed, and the system response time is long and easily affected by the learning rate leading to the lack of system stability, which often fails to achieve the desired control effect in practice. In this paper, we propose an active control algorithm with nearest-neighbor trap structure… More > Graphic Abstract