Salman A. Khan^1,*, Mohamed Mohandes^2,3, Shafiqur Rehman³, Ali Al-Shaikhi^2,4, Kashif Iqbal¹

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 553-581, 2025, DOI:10.32604/cmc.2025.064560 - 09 June 2025

Abstract Wind energy has emerged as a potential replacement for fossil fuel-based energy sources. To harness maximum wind energy, a crucial decision in the development of an efficient wind farm is the optimal layout design. This layout defines the specific locations of the turbines within the wind farm. The process of finding the optimal locations of turbines, in the presence of various technical and technological constraints, makes the wind farm layout design problem a complex optimization problem. This problem has traditionally been solved with nature-inspired algorithms with promising results. The performance and convergence of nature-inspired algorithms… More >

Atheer Alrammahi^1,2, Hedieh Sajedi^1,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 887-918, 2025, DOI:10.32604/cmc.2025.063866 - 09 June 2025

Abstract Ensuring digital media security through robust image watermarking is essential to prevent unauthorized distribution, tampering, and copyright infringement. This study introduces a novel hybrid watermarking framework that integrates Discrete Wavelet Transform (DWT), Redundant Discrete Wavelet Transform (RDWT), and Möbius Transformations (MT), with optimization of transformation parameters achieved via a Genetic Algorithm (GA). By combining frequency and spatial domain techniques, the proposed method significantly enhances both the imperceptibility and robustness of watermark embedding. The approach leverages DWT and RDWT for multi-resolution decomposition, enabling watermark insertion in frequency subbands that balance visibility and resistance to attacks. RDWT,… More >

Helen Shin Huey Wee, Nur Syazreen Ahmad^*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1301-1354, 2025, DOI:10.32604/cmes.2025.063611 - 30 May 2025

Abstract This paper reviews recent advancements in system identification methods for perturbed motorized systems, focusing on brushed DC motors, brushless DC motors, and permanent magnet synchronous motors. It examines data acquisition setups and evaluates conventional and metaheuristic optimization algorithms, highlighting their advantages, limitations, and applications. The paper explores emerging trends in model structures and parameter optimization techniques that address specific perturbations such as varying loads, noise, and friction. A comparative performance analysis is also included to assess several widely used optimization methods, including least squares (LS), particle swarm optimization (PSO), grey wolf optimizer (GWO), bat algorithm… More >

Wencheng Wang^1,2,*, Baoxin Yin^1,2, Lei Li^2,*, Lun Li¹, Hongtao Liu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1595-1616, 2025, DOI:10.32604/cmes.2025.063595 - 30 May 2025

Abstract In low-light environments, captured images often exhibit issues such as insufficient clarity and detail loss, which significantly degrade the accuracy of subsequent target recognition tasks. To tackle these challenges, this study presents a novel low-light image enhancement algorithm that leverages virtual hazy image generation through dehazing models based on statistical analysis. The proposed algorithm initiates the enhancement process by transforming the low-light image into a virtual hazy image, followed by image segmentation using a quadtree method. To improve the accuracy and robustness of atmospheric light estimation, the algorithm incorporates a genetic algorithm to optimize the… More >

Kun Li¹, Tianfu Li^2,*, Xiuwei Wang¹, Qingchun Meng¹, Zhenjie Wang¹, Jinyang Luo^1,2, Zhaohui Wang¹, Yuedong Yao²

Energy Engineering, Vol.122, No.6, pp. 2215-2238, 2025, DOI:10.32604/ee.2025.062876 - 29 May 2025

Abstract CO₂ flooding for enhanced oil recovery (EOR) not only enables underground carbon storage but also plays a critical role in tertiary oil recovery. However, its displacement efficiency is constrained by whether CO₂ and crude oil achieve miscibility, necessitating precise prediction of the minimum miscibility pressure (MMP) for CO₂-oil systems. Traditional methods, such as experimental measurements and empirical correlations, face challenges including time-consuming procedures and limited applicability. In contrast, artificial intelligence (AI) algorithms have emerged as superior alternatives due to their efficiency, broad applicability, and high prediction accuracy. This study employs four AI algorithms—Random Forest Regression (RFR), Genetic… More >

Huu-Tuong Ho¹, Thi-Thuy-Hoai Nguyen², Duong Nguyen Minh Huy³, Luong Vuong Nguyen^1,*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3945-3973, 2025, DOI:10.32604/cmc.2025.063099 - 19 May 2025

Abstract Natural Language Processing (NLP) has become essential in text classification, sentiment analysis, machine translation, and speech recognition applications. As these tasks become complex, traditional machine learning and deep learning models encounter challenges with optimization, parameter tuning, and handling large-scale, high-dimensional data. Bio-inspired algorithms, which mimic natural processes, offer robust optimization capabilities that can enhance NLP performance by improving feature selection, optimizing model parameters, and integrating adaptive learning mechanisms. This review explores the state-of-the-art applications of bio-inspired algorithms—such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO)—across core NLP tasks. We analyze More >

Iman S. Al-Mahdi¹, Saad M. Darwish^1,*, Magda M. Madbouly²

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 875-909, 2025, DOI:10.32604/cmes.2025.061623 - 11 April 2025

Abstract Heart disease prediction is a critical issue in healthcare, where accurate early diagnosis can save lives and reduce healthcare costs. The problem is inherently complex due to the high dimensionality of medical data, irrelevant or redundant features, and the variability in risk factors such as age, lifestyle, and medical history. These challenges often lead to inefficient and less accurate models. Traditional prediction methodologies face limitations in effectively handling large feature sets and optimizing classification performance, which can result in overfitting poor generalization, and high computational cost. This work proposes a novel classification model for heart… More >

Adil Yousif^*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2869-2892, 2025, DOI:10.32604/cmes.2025.059786 - 03 March 2025

Abstract The Internet of Things (IoT) has emerged as an important future technology. IoT-Fog is a new computing paradigm that processes IoT data on servers close to the source of the data. In IoT-Fog computing, resource allocation and independent task scheduling aim to deliver short response time services demanded by the IoT devices and performed by fog servers. The heterogeneity of the IoT-Fog resources and the huge amount of data that needs to be processed by the IoT-Fog tasks make scheduling fog computing tasks a challenging problem. This study proposes an Adaptive Firefly Algorithm (AFA) for… More >

Sudipta Debnath¹, Zahir Uddin Ahmed², Muhammad Ikhlaq^3,4,*, Md. Tanvir Khan⁵, Avneet Kaur⁶, Kuljeet Singh Grewal¹

Frontiers in Heat and Mass Transfer, Vol.23, No.1, pp. 71-94, 2025, DOI:10.32604/fhmt.2024.059734 - 26 February 2025

Abstract Impinging jet arrays are extensively used in numerous industrial operations, including the cooling of electronics, turbine blades, and other high-heat flux systems because of their superior heat transfer capabilities. Optimizing the design and operating parameters of such systems is essential to enhance cooling efficiency and achieve uniform pressure distribution, which can lead to improved system performance and energy savings. This paper presents two multi-objective optimization methodologies for a turbulent air jet impingement cooling system. The governing equations are resolved employing the commercial computational fluid dynamics (CFD) software ANSYS Fluent v17. The study focuses on four… More > Graphic Abstract

Hongliang Hao¹, Caifeng Wen^2,3, Feifei Xue^2,*, Hao Qiu¹, Ning Yang², Yuwen Zhang¹, Chaoyu Wang¹, Edwin E. Nyakilla¹

Energy Engineering, Vol.122, No.1, pp. 285-306, 2025, DOI:10.32604/ee.2024.057720 - 27 December 2024

Abstract Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources. This paper proposes a wind-solar hybrid energy storage system (HESS) to ensure a stable supply grid for a longer period. A multi-objective genetic algorithm (MOGA) and state of charge (SOC) region division for the batteries are introduced to solve the objective function and configuration of the system capacity, respectively. MATLAB/Simulink was used for simulation test. The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system, with a combination of a 300 More >