Zijian Liu¹, Yong Shi², Chuanqi Li¹, Xiliang Zhang^3,*, Jian Zhou¹, Manoj Khandelwal^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 153-183, 2025, DOI:10.32604/cmes.2025.062426 - 11 April 2025

Abstract Given the growing concern over global warming and the critical role of carbon dioxide (CO₂) in this phenomenon, the study of CO₂-induced alterations in coal strength has garnered significant attention due to its implications for carbon sequestration. A large number of experiments have proved that CO₂ interaction time (T), saturation pressure (P) and other parameters have significant effects on coal strength. However, accurate evaluation of CO₂-induced alterations in coal strength is still a difficult problem, so it is particularly important to establish accurate and efficient prediction models. This study explored the application of advanced machine learning (ML)… More >

Murat Cikan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 673-721, 2025, DOI:10.32604/cmes.2025.061699 - 11 April 2025

Abstract This study examines various issues arising in three-phase unbalanced power distribution networks (PDNs) using a comprehensive optimization approach. With the integration of renewable energy sources, increasing energy demands, and the adoption of smart grid technologies, power systems are undergoing a rapid transformation, making the need for efficient, reliable, and sustainable distribution networks increasingly critical. In this paper, the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms. Among these advanced search algorithms, the Bonobo Optimizer (BO) has demonstrated superior performance in handling the complexities of unbalanced power… More >

Robertas Damasevicius^*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 1493-1538, 2025, DOI:10.32604/cmc.2024.057431 - 17 February 2025

Abstract Heuristic optimization algorithms have been widely used in solving complex optimization problems in various fields such as engineering, economics, and computer science. These algorithms are designed to find high-quality solutions efficiently by balancing exploration of the search space and exploitation of promising solutions. While heuristic optimization algorithms vary in their specific details, they often exhibit common patterns that are essential to their effectiveness. This paper aims to analyze and explore common patterns in heuristic optimization algorithms. Through a comprehensive review of the literature, we identify the patterns that are commonly observed in these algorithms, including… More >

Elif Varol Altay, Osman Altay, Yusuf Özçevik^*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 1039-1094, 2024, DOI:10.32604/cmes.2023.029404 - 30 December 2023

Abstract Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve. Such design problems are widely experienced in many engineering fields, such as industry, automotive, construction, machinery, and interdisciplinary research. However, there are established optimization techniques that have shown effectiveness in addressing these types of issues. This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues. The algorithms used in the study are listed as: transient search optimization (TSO), equilibrium optimizer (EO), grey wolf optimizer… More >

Tianfeng Xu¹, Tao Wang¹, Chengming Ye², Jing Zhang¹, Peng Xi¹, Yunhui Chen², Gengwu Zhang^3,*

Energy Engineering, Vol.120, No.11, pp. 2629-2650, 2023, DOI:10.32604/ee.2023.027537 - 31 October 2023

Abstract In order to improve the reliability of power supply, the sophisticated design of the structure of electric cable network has become an important issue for modern urban distribution networks. In this paper, an electric cable path planning model based on heuristic optimization algorithm considering mixed-land scenario is proposed. Firstly, based on different land samples, the kernel density estimation (KDE) and the analytic hierarchy process (AHP) are used to estimate the construction cost of each unit grid, in order to construct the objective function of comprehensive investment for electric cable loop network. Then, the ant colony More >

Saleh Ateeq Almutairi^*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2599-2624, 2023, DOI:10.32604/csse.2023.041609 - 28 July 2023

Abstract Heart disease is a primary cause of death worldwide and is notoriously difficult to cure without a proper diagnosis. Hence, machine learning (ML) can reduce and better understand symptoms associated with heart disease. This study aims to develop a framework for the automatic and accurate classification of heart disease utilizing machine learning algorithms, grid search (GS), and the Aquila optimization algorithm. In the proposed approach, feature selection is used to identify characteristics of heart disease by using a method for dimensionality reduction. First, feature selection is accomplished with the help of the Aquila algorithm. Then,… More >

Afrah Al-Bossly^*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6395-6408, 2023, DOI:10.32604/cmc.2023.028433 - 29 April 2023

Abstract Due to the drastic increase in global population as well as economy, electricity demand becomes considerably high. The recently developed smart grid (SG) technology has the ability to minimize power loss at the time of power distribution. Machine learning (ML) and deep learning (DL) models can be effectually developed for the design of SG stability techniques. This article introduces a new Social Spider Optimization with Deep Learning Enabled Statistical Analysis for Smart Grid Stability (SSODLSA-SGS) prediction model. Primarily, class imbalance data handling process is performed using Synthetic minority oversampling technique (SMOTE) technique. The SSODLSA-SGS model… More >

Binwen Zhu¹, Qifang Luo^1,3,*, Yongquan Zhou^1,2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 385-413, 2023, DOI:10.32604/cmes.2023.026097 - 23 April 2023

Abstract With the rapid development of communication technology, the problem of antenna array optimization plays a crucial role. Among many types of antennas, line antenna arrays (LAA) are the most commonly applied, but the side lobe level (SLL) reduction is still a challenging problem. In the radiation process of the linear antenna array, the high side lobe level will interfere with the intensity of the antenna target radiation direction. Many conventional methods are ineffective in obtaining the maximum side lobe level in synthesis, and this paper proposed a quantum equilibrium optimizer (QEO) algorithm for line antenna… More >

Yuxin Chen¹, Weixun Yong¹, Chuanqi Li², Jian Zhou^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2507-2526, 2023, DOI:10.32604/cmes.2023.025714 - 09 March 2023

Abstract After the excavation of the roadway, the original stress balance is destroyed, resulting in the redistribution of stress and the formation of an excavation damaged zone (EDZ) around the roadway. The thickness of EDZ is the key basis for roadway stability discrimination and support structure design, and it is of great engineering significance to accurately predict the thickness of EDZ. Considering the advantages of machine learning (ML) in dealing with high-dimensional, nonlinear problems, a hybrid prediction model based on the random forest (RF) algorithm is developed in this paper. The model used the dragonfly algorithm… More >

Khaled A. Fathy, Humam K. Yaseen^*, Mohammad T. Abou-Kreisha, Kamal A. ElDahshan

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1527-1545, 2023, DOI:10.32604/cmc.2023.036322 - 06 February 2023

Abstract Some human diseases are recognized through of each type of White Blood Cell (WBC) count, so detecting and classifying each type is important for human healthcare. The main aim of this paper is to propose a computer-aided WBCs utility analysis tool designed, developed, and evaluated to classify WBCs into five types namely neutrophils, eosinophils, lymphocytes, monocytes, and basophils. Using a computer-artificial model reduces resource and time consumption. Various pre-trained deep learning models have been used to extract features, including AlexNet, Visual Geometry Group (VGG), Residual Network (ResNet), which belong to different taxonomy types of deep… More >