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  • Open Access

    ARTICLE

    A Stacked BWO-NIGP Framework for Robust and Accurate SOH Estimation of Lithium-Ion Batteries under Noisy and Small-Sample Scenarios

    Pu Yang1,*, Wanning Yan1, Rong Li1, Lei Chen2, Lijie Guo2

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 699-725, 2025, DOI:10.32604/cmc.2025.064947 - 09 June 2025

    Abstract Lithium-ion batteries (LIBs) have been widely used in mobile energy storage systems because of their high energy density, long life, and strong environmental adaptability. Accurately estimating the state of health (SOH) for LIBs is promising and has been extensively studied for many years. However, the current prediction methods are susceptible to noise interference, and the estimation accuracy has room for improvement. Motivated by this, this paper proposes a novel battery SOH estimation method, the Beluga Whale Optimization (BWO) and Noise-Input Gaussian Process (NIGP) Stacked Model (BGNSM). This method integrates the BWO-optimized Gaussian Process Regression (GPR)… More >

  • Open Access

    ARTICLE

    FSFS: A Novel Statistical Approach for Fair and Trustworthy Impactful Feature Selection in Artificial Intelligence Models

    Ali Hamid Farea1,*, Iman Askerzade1,2, Omar H. Alhazmi3, Savaş Takan4

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1457-1484, 2025, DOI:10.32604/cmc.2025.064872 - 09 June 2025

    Abstract Feature selection (FS) is a pivotal pre-processing step in developing data-driven models, influencing reliability, performance and optimization. Although existing FS techniques can yield high-performance metrics for certain models, they do not invariably guarantee the extraction of the most critical or impactful features. Prior literature underscores the significance of equitable FS practices and has proposed diverse methodologies for the identification of appropriate features. However, the challenge of discerning the most relevant and influential features persists, particularly in the context of the exponential growth and heterogeneity of big data—a challenge that is increasingly salient in modern artificial… More >

  • Open Access

    ARTICLE

    Toward Intrusion Detection of Industrial Cyber-Physical System: A Hybrid Approach Based on System State and Network Traffic Abnormality Monitoring

    Junbin He1,2, Wuxia Zhang3, Xianyi Liu1, Jinping Liu2,*, Guangyi Yang4

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1227-1252, 2025, DOI:10.32604/cmc.2025.064402 - 09 June 2025

    Abstract The integration of cloud computing into traditional industrial control systems is accelerating the evolution of Industrial Cyber-Physical System (ICPS), enhancing intelligence and autonomy. However, this transition also expands the attack surface, introducing critical security vulnerabilities. To address these challenges, this article proposes a hybrid intrusion detection scheme for securing ICPSs that combines system state anomaly and network traffic anomaly detection. Specifically, an improved variation-Bayesian-based noise covariance-adaptive nonlinear Kalman filtering (IVB-NCA-NLKF) method is developed to model nonlinear system dynamics, enabling optimal state estimation in multi-sensor ICPS environments. Intrusions within the physical sensing system are identified by More >

  • Open Access

    ARTICLE

    Reinforcement Learning for Solving the Knapsack Problem

    Zhenfu Zhang1, Haiyan Yin2, Liudong Zuo3, Pan Lai1,*

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 919-936, 2025, DOI:10.32604/cmc.2025.062980 - 09 June 2025

    Abstract The knapsack problem is a classical combinatorial optimization problem widely encountered in areas such as logistics, resource allocation, and portfolio optimization. Traditional methods, including dynamic programming (DP) and greedy algorithms, have been effective in solving small problem instances but often struggle with scalability and efficiency as the problem size increases. DP, for instance, has exponential time complexity and can become computationally prohibitive for large problem instances. On the other hand, greedy algorithms offer faster solutions but may not always yield the optimal results, especially when the problem involves complex constraints or large numbers of items.… More >

  • Open Access

    REVIEW

    State-of-the-Art Review on Seepage Instability and Water Inrush Mechanisms in Karst Collapse Columns

    Zhengzheng Cao1, Shuaiyang Zhang1, Cunhan Huang2,*, Feng Du3,4, Zhenhua Li3,4, Shuren Wang1, Wenqiang Wang3,4, Minglei Zhai3,4

    FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.5, pp. 1007-1028, 2025, DOI:10.32604/fdmp.2025.062738 - 30 May 2025

    Abstract Karst collapse columns typically appear unpredictably and without a uniform spatial arrangement, posing challenges for mining operations and water inrush risk assessment. As major structural pathways for mine water inrush, they are responsible for some of the most frequent and severe water-related disasters in coal mining. Understanding the mechanisms of water inrush in these collapse columns is therefore essential for effective disaster prevention and control, making it a key research priority. Additionally, investigating the developmental characteristics of collapse columns is crucial for analyzing seepage instability mechanisms. In such a context, this paper provides a comprehensive… More > Graphic Abstract

    State-of-the-Art Review on Seepage Instability and Water Inrush Mechanisms in Karst Collapse Columns

  • Open Access

    ARTICLE

    Demand Forecasting of a Microgrid-Powered Electric Vehicle Charging Station Enabled by Emerging Technologies and Deep Recurrent Neural Networks

    Sahbi Boubaker1,*, Adel Mellit2,3,*, Nejib Ghazouani4, Walid Meskine5, Mohamed Benghanem6, Habib Kraiem7,8

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 2237-2259, 2025, DOI:10.32604/cmes.2025.064530 - 30 May 2025

    Abstract Electric vehicles (EVs) are gradually being deployed in the transportation sector. Although they have a high impact on reducing greenhouse gas emissions, their penetration is challenged by their random energy demand and difficult scheduling of their optimal charging. To cope with these problems, this paper presents a novel approach for photovoltaic grid-connected microgrid EV charging station energy demand forecasting. The present study is part of a comprehensive framework involving emerging technologies such as drones and artificial intelligence designed to support the EVs’ charging scheduling task. By using predictive algorithms for solar generation and load demand… More >

  • Open Access

    ARTICLE

    Developed Time-Optimal Model Predictive Static Programming Method with Fish Swarm Optimization for Near-Space Vehicle

    Yuanzhuo Wang, Honghua Dai*

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1463-1484, 2025, DOI:10.32604/cmes.2025.064416 - 30 May 2025

    Abstract To establish the optimal reference trajectory for a near-space vehicle under free terminal time, a time-optimal model predictive static programming method is proposed with adaptive fish swarm optimization. First, the model predictive static programming method is developed by incorporating neighboring terms and trust region, enabling rapid generation of precise optimal solutions. Next, an adaptive fish swarm optimization technique is employed to identify a sub-optimal solution, while a momentum gradient descent method with learning rate decay ensures the convergence to the global optimal solution. To validate the feasibility and accuracy of the proposed method, a near-space More >

  • Open Access

    EDITORIAL

    AI-Driven Interaction and Collaborative Optimization of Vehicle, Charging Station and Grid: Challenges and Prospects

    Bo Yang1,*, Zhe Jiang1, Jianfeng Wen2, Ning Yang3, Kaiping Qu4, Shuai Zhou5

    Energy Engineering, Vol.122, No.6, pp. 2187-2195, 2025, DOI:10.32604/ee.2025.065489 - 29 May 2025

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Experimental and Numerical Simulation Research on Aerodynamic Field of Integrated Exhaust End of Natural Gas Distributed Energy Station

    Shuang Li1, Suoying He2, Shen Cheng1,*, Jiarui Wu1, Ruiting Meng1

    Energy Engineering, Vol.122, No.6, pp. 2309-2335, 2025, DOI:10.32604/ee.2025.062216 - 29 May 2025

    Abstract In view of the situation of multi-temperature, multi-medium and multi-discharge equipment on the integrated exhaust end platform of a natural gas distributed energy station, which is compact in layout, mutual influence, complex aerodynamic field and complex heat and mass transfer field, the temperature field and aerodynamic field of the platform were comprehensively studied through field experiments and numerical simulation. The research results show that the high temperature flue gas discharged from the chimney is hindered by the chimney cap and returns downward. The noise reduction walls around the chimney make the top of the platform… More >

  • Open Access

    ARTICLE

    Gallic acid suppresses esophageal squamous cell carcinoma progression and enhances cisplatin chemosensitivity through IL-6/STAT3/Notch pathway

    NURAN BEDOLLA#, HAO WU#, LINYU LIU, XUETING LIU, YANLI REN*

    Oncology Research, Vol.33, No.6, pp. 1473-1484, 2025, DOI:10.32604/or.2025.060151 - 29 May 2025

    Abstract Background: Gallic acid (GA), a plant-derived polyphenol, possesses diverse biological functions such as reducing inflammation and against tumors. Currently, the influence of GA on the resistance of esophageal squamous cell carcinoma (ESCC) cells to cisplatin (DDP) is not well understood. Methods: Cell counting kit-8 assay examined how GA affected KYSE30 and TE-1 cell viability. 5-Ethynyl-2′-deoxyuridine and TdT-mediated dUTP Nick-End labeling staining detected cell proliferation and apoptosis. Clone formation assay, flow cytometry, Carboxyfluorescein diacetate succinimidyl ester fluorescent probes, and Transwell assay determined cell biological properties, and 2′,7′-Dichlorofluorescin diacetate (DCFH-DA) fluorescent probes detected oxidative stress levels. Signal… More > Graphic Abstract

    Gallic acid suppresses esophageal squamous cell carcinoma progression and enhances cisplatin chemosensitivity through IL-6/STAT3/Notch pathway

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