Amrutanshu Panigrahi¹, Abhilash Pati¹, Bibhuprasad Sahu², Ashis Kumar Pati³, Subrata Chowdhury⁴, Khursheed Aurangzeb^5,*, Nadeem Javaid⁶, Sheraz Aslam^7,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1633-1657, 2025, DOI:10.32604/cmc.2025.063562 - 09 June 2025

Abstract The integration of IoT and Deep Learning (DL) has significantly advanced real-time health monitoring and predictive maintenance in prognostic and health management (PHM). Electrocardiograms (ECGs) are widely used for cardiovascular disease (CVD) diagnosis, but fluctuating signal patterns make classification challenging. Computer-assisted automated diagnostic tools that enhance ECG signal categorization using sophisticated algorithms and machine learning are helping healthcare practitioners manage greater patient populations. With this motivation, the study proposes a DL framework leveraging the PTB-XL ECG dataset to improve CVD diagnosis. Deep Transfer Learning (DTL) techniques extract features, followed by feature fusion to eliminate redundancy… More >

Liang Tang¹, Hongwei Wang¹, Xinyuan Zhu¹, Jiying Liu^2,*, Kaiyue Li^2,*

Energy Engineering, Vol.122, No.6, pp. 2257-2289, 2025, DOI:10.32604/ee.2025.063918 - 29 May 2025

Abstract The intermittency and volatility of wind and photovoltaic power generation exacerbate issues such as wind and solar curtailment, hindering the efficient utilization of renewable energy and the low-carbon development of energy systems. To enhance the consumption capacity of green power, the green power system consumption optimization scheduling model (GPS-COSM) is proposed, which comprehensively integrates green power system, electric boiler, combined heat and power unit, thermal energy storage, and electrical energy storage. The optimization objectives are to minimize operating cost, minimize carbon emission, and maximize the consumption of wind and solar curtailment. The multi-objective particle swarm… More >

Lang Qin¹, Zhengrui Jiang¹, Xueshu Xing², Xiao Wang¹, Yaohua Yin², Yuhui Zhou², Zhiqin He^1,*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5279-5298, 2025, DOI:10.32604/cmc.2025.063358 - 19 May 2025

Abstract In permanent magnet synchronous motor (PMSM) control, the jitter problem affects the system performance, so a novel reaching law is proposed to construct a non-singular fast terminal sliding mode controller (NFTSMC) to reduce the jitter. To enhance the immunity of the system, a disturbance observer is designed to observe and compensate for the disturbance to the sliding mode controller. In addition, considering that the controller parameters are difficult to adjust, and the traditional zebra optimization algorithm (ZOA) is prone to converge prematurely and fall into local optimum when solving the optimal solution, the improved zebra… More >

Hui Xu, Jiahui Chen^*, Zhonghao Hu

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4495-4513, 2025, DOI:10.32604/cmc.2025.062189 - 19 May 2025

Abstract Nowadays, abnormal traffic detection for Software-Defined Networking (SDN) faces the challenges of large data volume and high dimensionality. Since traditional machine learning-based detection methods have the problem of data redundancy, the Metaheuristic Algorithm (MA) is introduced to select features before machine learning to reduce the dimensionality of data. Since a Tyrannosaurus Optimization Algorithm (TROA) has the advantages of few parameters, simple implementation, and fast convergence, and it shows better results in feature selection, TROA can be applied to abnormal traffic detection for SDN. However, TROA suffers from insufficient global search capability, is easily trapped in… More >

Shaoming Qiu, Jingjie He, Yan Wang^*, Bicong E

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4879-4898, 2025, DOI:10.32604/cmc.2025.061532 - 19 May 2025

Abstract Software defect prediction (SDP) aims to find a reliable method to predict defects in specific software projects and help software engineers allocate limited resources to release high-quality software products. Software defect prediction can be effectively performed using traditional features, but there are some redundant or irrelevant features in them (the presence or absence of this feature has little effect on the prediction results). These problems can be solved using feature selection. However, existing feature selection methods have shortcomings such as insignificant dimensionality reduction effect and low classification accuracy of the selected optimal feature subset. In… More >

Wenli Lei^1,2,*, Xinghao Wu^1,2, Kun Jia^1,2, Jinping Han^1,2

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5679-5698, 2025, DOI:10.32604/cmc.2025.061268 - 19 May 2025

Abstract Aiming to address the limitations of the standard Chimp Optimization Algorithm (ChOA), such as inadequate search ability and susceptibility to local optima in Unmanned Aerial Vehicle (UAV) path planning, this paper proposes a three-dimensional path planning method for UAVs based on the Improved Chimp Optimization Algorithm (IChOA). First, this paper models the terrain and obstacle environments spatially and formulates the total UAV flight cost function according to the constraints, transforming the path planning problem into an optimization problem with multiple constraints. Second, this paper enhances the diversity of the chimpanzee population by applying the Sine… More >

Zhiyuan Zhang¹, Yongjun Wu¹, Xiqin Li¹, Minghui Song¹, Guangwu Zhang², Ziren Wang^3,*, Wei Li³

Energy Engineering, Vol.122, No.5, pp. 1919-1948, 2025, DOI:10.32604/ee.2025.063178 - 25 April 2025

Abstract The park-level integrated energy system (PIES) is essential for achieving carbon neutrality by managing multi-energy supply and demand while enhancing renewable energy integration. However, current carbon trading mechanisms lack sufficient incentives for emission reductions, and traditional optimization algorithms often face challenges with convergence and local optima in complex PIES scheduling. To address these issues, this paper introduces a low-carbon dispatch strategy that combines a reward-penalty tiered carbon trading model with P2G-CCS integration, hydrogen utilization, and the Secretary Bird Optimization Algorithm (SBOA). Key innovations include: (1) A dynamic reward-penalty carbon trading mechanism with coefficients (μ = 0.2,… More >

Tareq Hamadneh¹, Belal Batiha², Omar Alsayyed³, Widi Aribowo⁴, Zeinab Montazeri⁵, Mohammad Dehghani^5,*, Frank Werner^6,*, Haider Ali⁷, Riyadh Kareem Jawad⁸, Ibraheem Kasim Ibraheem⁹, Kei Eguchi¹⁰

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2677-2718, 2025, DOI:10.32604/cmc.2025.064087 - 16 April 2025

Abstract In this study, a completely different approach to optimization is introduced through the development of a novel metaheuristic algorithm called the Barber Optimization Algorithm (BaOA). Inspired by the human interactions between barbers and customers, BaOA captures two key processes: the customer’s selection of a hairstyle and the detailed refinement during the haircut. These processes are translated into a mathematical framework that forms the foundation of BaOA, consisting of two critical phases: exploration, representing the creative selection process, and exploitation, which focuses on refining details for optimization. The performance of BaOA is evaluated using 52 standard… More >

Mengjiao Wei^1,*, Wenyu Liu²

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2505-2523, 2025, DOI:10.32604/cmc.2025.060887 - 16 April 2025

Abstract In recent years, decomposition-based evolutionary algorithms have become popular algorithms for solving multi-objective problems in real-life scenarios. In these algorithms, the reference vectors of the Penalty-Based boundary intersection (PBI) are distributed parallelly while those based on the normal boundary intersection (NBI) are distributed radially in a conical shape in the objective space. To improve the problem-solving effectiveness of multi-objective optimization algorithms in engineering applications, this paper addresses the improvement of the Collaborative Decomposition (CoD) method, a multi-objective decomposition technique that integrates PBI and NBI, and combines it with the Elephant Clan Optimization Algorithm, introducing the… More >

Xiangyang Cao^1,2, Yaojie Zheng^1,2, Hanbin Xiao^1,2,*, Min Xiao^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 289-334, 2025, DOI:10.32604/cmes.2025.063954 - 11 April 2025

Abstract This study investigates the Maximum Power Point Tracking (MPPT) control method of offshore wind-photovoltaic hybrid power generation system with offshore crane-assisted. A new algorithm of Global Fast Integral Sliding Mode Control (GFISMC) is proposed based on the tip speed ratio method and sliding mode control. The algorithm uses fast integral sliding mode surface and fuzzy fast switching control items to ensure that the offshore wind power generation system can track the maximum power point quickly and with low jitter. An offshore wind power generation system model is presented to verify the algorithm effect. An offshore More >