Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (3,311)
  • Open Access

    ARTICLE

    Short-Term Photovoltaic Power Prediction Based on Multi-Stage Temporal Feature Learning

    Qiang Wang1, Hao Cheng2, Wenrui Zhang2,*, Guangxi Li3, Fan Xu2, Dianhao Chen4, Haixiang Zang4

    Energy Engineering, Vol.122, No.2, pp. 747-764, 2025, DOI:10.32604/ee.2025.059533 - 31 January 2025

    Abstract Harnessing solar power is essential for addressing the dual challenges of global warming and the depletion of traditional energy sources. However, the fluctuations and intermittency of photovoltaic (PV) power pose challenges for its extensive incorporation into power grids. Thus, enhancing the precision of PV power prediction is particularly important. Although existing studies have made progress in short-term prediction, issues persist, particularly in the underutilization of temporal features and the neglect of correlations between satellite cloud images and PV power data. These factors hinder improvements in PV power prediction performance. To overcome these challenges, this paper… More >

  • 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

    REVIEW

    The Electric Vehicle Surge: Effective Solutions for Charging Challenges with Advanced Converter Technologies

    Rajanand Patnaik Narasipuram1,*, Md M. Pasha2, Saleha Tabassum3, Amit Singh Tandon4

    Energy Engineering, Vol.122, No.2, pp. 431-469, 2025, DOI:10.32604/ee.2025.055134 - 31 January 2025

    Abstract The global adoption of Electric Vehicles (EVs) is on the rise due to their advanced features, with projections indicating they will soon dominate the private vehicle market. However, improper management of EV charging can lead to significant issues. This paper reviews the development of high-power, reliable charging solutions by examining the converter topologies used in rectifiers and converters that transfer electricity from the grid to EV batteries. It covers technical details, ongoing developments, and challenges related to these topologies and control strategies. The integration of rapid charging stations has introduced various Power Quality (PQ) issues,… More >

  • Open Access

    ARTICLE

    Changes in Depression, Anxiety, and Stress Levels during a Religious Period: A Prospective Cohort Study

    Ibrahim M. Gosadi*

    International Journal of Mental Health Promotion, Vol.27, No.1, pp. 41-49, 2025, DOI:10.32604/ijmhp.2024.059822 - 31 January 2025

    Abstract Objective: There is conflicting evidence suggesting an association between Ramadan and mental health. Aim: This study aims to assess changes in depression, anxiety, and stress levels during Ramadan among university students from Saudi Arabia and to measure the magnitude of change in these levels according to gender. Methods: This study is a prospective cohort study. Data was collected using a structured questionnaire that measured demographic data of the students, and levels of depression, anxiety, and stress utilizing the short form of the Depression Anxiety Stress Scales questionnaire (DASS 21). The assessments were performed starting from the… More >

  • Open Access

    REVIEW

    Plates, Beams and Shells Reinforced by CNTs or GPLs: A Review on Their Structural Behavior and Computational Methods

    Mohammad Javad Bayat1, Amin Kalhori2, Kamran Asemi1,*, Masoud Babaei3

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1351-1458, 2025, DOI:10.32604/cmes.2025.060222 - 27 January 2025

    Abstract Since the initial observation of carbon nanotubes (CNTs) and graphene platelets (GPLs) in the 1990 and 2000s, the demand for high-performance structural applications and multifunctional materials has driven significant interest in composite structures reinforced with GPLs and CNTs. Incorporating these nanofillers into matrix materials markedly enhances the mechanical properties of the structures. To further improve efficiency and functionality, functionally graded (FG) distributions of CNTs and GPLs have been proposed. This study presents an extensive review of computational approaches developed to predict the global behavior of composite structural components enhanced with CNT and GPL nanofillers. The… More >

  • Open Access

    ARTICLE

    Hybrid DF and SIR Forwarding Strategy in Conventional and Distributed Alamouti Space-Time Coded Cooperative Networks

    Slim Chaoui1,*, Omar Alruwaili1, Faeiz Alserhani1, Haifa Harrouch2

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1933-1954, 2025, DOI:10.32604/cmes.2025.059346 - 27 January 2025

    Abstract In this paper, we propose a hybrid decode-and-forward and soft information relaying (HDFSIR) strategy to mitigate error propagation in coded cooperative communications. In the HDFSIR approach, the relay operates in decode-and-forward (DF) mode when it successfully decodes the received message; otherwise, it switches to soft information relaying (SIR) mode. The benefits of the DF and SIR forwarding strategies are combined to achieve better performance than deploying the DF or SIR strategy alone. Closed-form expressions for the outage probability and symbol error rate (SER) are derived for coded cooperative communication with HDFSIR and energy-harvesting relays. Additionally,… More >

  • Open Access

    ARTICLE

    Magneto-Electro-Elastic Analysis of Doubly-Curved Shells: Higher-Order Equivalent Layer-Wise Formulation

    Francesco Tornabene*, Matteo Viscoti, Rossana Dimitri

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1767-1838, 2025, DOI:10.32604/cmes.2024.058842 - 27 January 2025

    Abstract Recent engineering applications increasingly adopt smart materials, whose mechanical responses are sensitive to magnetic and electric fields. In this context, new and computationally efficient modeling strategies are essential to predict the multiphysic behavior of advanced structures accurately. Therefore, the manuscript presents a higher-order formulation for the static analysis of laminated anisotropic magneto-electro-elastic doubly-curved shell structures. The fundamental relations account for the full coupling between the electric field, magnetic field, and mechanical elasticity. The configuration variables are expanded along the thickness direction using a generalized formulation based on the Equivalent Layer-Wise approach. Higher-order polynomials are selected,… More >

  • Open Access

    REVIEW

    Enhancing Evapotranspiration Estimation: A Bibliometric and Systematic Review of Hybrid Neural Networks in Water Resource Management

    Moein Tosan1, Mohammad Reza Gharib2,*, Nasrin Fathollahzadeh Attar3, Ali Maroosi4

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1109-1154, 2025, DOI:10.32604/cmes.2025.058595 - 27 January 2025

    Abstract Accurate estimation of evapotranspiration (ET) is crucial for efficient water resource management, particularly in the face of climate change and increasing water scarcity. This study performs a bibliometric analysis of 352 articles and a systematic review of 35 peer-reviewed papers, selected according to PRISMA guidelines, to evaluate the performance of Hybrid Artificial Neural Networks (HANNs) in ET estimation. The findings demonstrate that HANNs, particularly those combining Multilayer Perceptrons (MLPs), Recurrent Neural Networks (RNNs), and Convolutional Neural Networks (CNNs), are highly effective in capturing the complex nonlinear relationships and temporal dependencies characteristic of hydrological processes. These… More > Graphic Abstract

    Enhancing Evapotranspiration Estimation: A Bibliometric and Systematic Review of Hybrid Neural Networks in Water Resource Management

  • Open Access

    ARTICLE

    From Imperfection to Perfection: Advanced 3D Facial Reconstruction Using MICA Models and Self-Supervision Learning

    Thinh D. Le, Duong Q. Nguyen, Phuong D. Nguyen, H. Nguyen-Xuan*

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1459-1479, 2025, DOI:10.32604/cmes.2024.056753 - 27 January 2025

    Abstract Research on reconstructing imperfect faces is a challenging task. In this study, we explore a data-driven approach using a pre-trained MICA (MetrIC fAce) model combined with 3D printing to address this challenge. We propose a training strategy that utilizes the pre-trained MICA model and self-supervised learning techniques to improve accuracy and reduce the time needed for 3D facial structure reconstruction. Our results demonstrate high accuracy, evaluated by the geometric loss function and various statistical measures. To showcase the effectiveness of the approach, we used 3D printing to create a model that covers facial wounds. The More >

  • Open Access

    RETRACTION

    Retraction: The Crime Scene Tools Identification Algorithm Based on GVF-Harris-SIFT and KNN

    Nan Pan1,*, Dilin Pan2, Yi Liu2

    Intelligent Automation & Soft Computing, Vol.40, pp. 147-147, 2025, DOI:10.32604/iasc.2025.062708 - 29 January 2025

    Abstract This article has no abstract. More >

Displaying 1-10 on page 1 of 3311. Per Page