Shiguang Hu^1,2, Le Ru^1,2,*, Bo Lu^1,2, Zhenhua Wang³, Xiaolin Zhao^1,2, Wenfei Wang^1,2, Hailong Xi^1,2

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1879-1903, 2024, DOI:10.32604/cmc.2024.056110 - 15 October 2024

Abstract The strategy evolution process of game players is highly uncertain due to random emergent situations and other external disturbances. This paper investigates the issue of strategy interaction and behavioral decision-making among game players in simulated confrontation scenarios within a random interference environment. It considers the possible risks that random disturbances may pose to the autonomous decision-making of game players, as well as the impact of participants’ manipulative behaviors on the state changes of the players. A nonlinear mathematical model is established to describe the strategy decision-making process of the participants in this scenario. Subsequently, the… More >

Sayat Ibrayev¹, Batyrkhan Omarov^1,2,3,*, Arman Ibrayeva¹, Zeinel Momynkulov^1,2

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 229-249, 2024, DOI:10.32604/cmc.2024.053075 - 15 October 2024

Abstract This research paper presents a comprehensive investigation into the effectiveness of the DeepSurNet-NSGA II (Deep Surrogate Model-Assisted Non-dominated Sorting Genetic Algorithm II) for solving complex multi-objective optimization problems, with a particular focus on robotic leg-linkage design. The study introduces an innovative approach that integrates deep learning-based surrogate models with the robust Non-dominated Sorting Genetic Algorithm II, aiming to enhance the efficiency and precision of the optimization process. Through a series of empirical experiments and algorithmic analyses, the paper demonstrates a high degree of correlation between solutions generated by the DeepSurNet-NSGA II and those obtained from… More >

Shoukai Lin^1,3,4,*, Yifan Xiong², Shichang Xu^1,2, Manegdebwaoaga Arthur Fabrice Kabore², Fan Lin⁵, Fuxiang Qiu^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1485-1502, 2024, DOI:10.32604/phyton.2024.050990 - 30 July 2024

Abstract The SWEET (sugar will eventually be exported transporter) family proteins are a recently identified class of sugar transporters that are essential for various physiological processes. Although the functions of the SWEET proteins have been identified in a number of species, to date, there have been no reports of the functions of the SWEET genes in woodland strawberries (Fragaria vesca). In this study, we identified 15 genes that were highly homologous to the A. thaliana AtSWEET genes and designated them as FvSWEET1–FvSWEET15. We then conducted a structural and evolutionary analysis of these 15 FvSWEET genes. The phylogenetic analysis enabled us… More >

Hongjiang Wang¹, Qingze Shen^2,*, Qin Dai¹, Yingcai Gao², Jing Gao², Tian Zhang^3,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 625-642, 2024, DOI:10.32604/cmc.2024.051757 - 18 July 2024

Abstract Deep learning has emerged in many practical applications, such as image classification, fault diagnosis, and object detection. More recently, convolutional neural networks (CNNs), representative models of deep learning, have been used to solve fault detection. However, the current design of CNNs for fault detection of wind turbine blades is highly dependent on domain knowledge and requires a large amount of trial and error. For this reason, an evolutionary YOLOv8 network has been developed to automatically find the network architecture for wind turbine blade-based fault detection. YOLOv8 is a CNN-backed object detection model. Specifically, to reduce… More >

Lin Chen¹, Jiaming Zhu¹, Yuting Xu¹, Huanqin Zheng¹, Shen Su^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2373-2395, 2024, DOI:10.32604/cmes.2024.049996 - 08 July 2024

Abstract In the information age, electronic documents (e-documents) have become a popular alternative to paper documents due to their lower costs, higher dissemination rates, and ease of knowledge sharing. However, digital copyright infringements occur frequently due to the ease of copying, which not only infringes on the rights of creators but also weakens their creative enthusiasm. Therefore, it is crucial to establish an e-document sharing system that enforces copyright protection. However, the existing centralized system has outstanding vulnerabilities, and the plagiarism detection algorithm used cannot fully detect the context, semantics, style, and other factors of the… More >

Javaid Ali¹, Armando Ciancio², Kashif Ali Khan³, Nauman Raza^4,5, Haci Mehmet Baskonus^6,*, Muhammad Luqman¹, Zafar-Ullah Khan⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2275-2296, 2024, DOI:10.32604/cmes.2024.046923 - 08 July 2024

Abstract This study proposes a structure-preserving evolutionary framework to find a semi-analytical approximate solution for a nonlinear cervical cancer epidemic (CCE) model. The underlying CCE model lacks a closed-form exact solution. Numerical solutions obtained through traditional finite difference schemes do not ensure the preservation of the model’s necessary properties, such as positivity, boundedness, and feasibility. Therefore, the development of structure-preserving semi-analytical approaches is always necessary. This research introduces an intelligently supervised computational paradigm to solve the underlying CCE model’s physical properties by formulating an equivalent unconstrained optimization problem. Singularity-free safe Padé rational functions approximate the mathematical More >

Song Deng^1,*, Yiming Yuan²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3679-3697, 2024, DOI:10.32604/cmc.2024.052008 - 20 June 2024

Abstract Malicious attacks against data are unavoidable in the interconnected, open and shared Energy Internet (EI), Intrusion tolerant techniques are critical to the data security of EI. Existing intrusion tolerant techniques suffered from problems such as low adaptability, policy lag, and difficulty in determining the degree of tolerance. To address these issues, we propose a novel adaptive intrusion tolerance model based on game theory that enjoys two-fold ideas: 1) it constructs an improved replica of the intrusion tolerance model of the dynamic equation evolution game to induce incentive weights; and 2) it combines a tournament competition More >

Chen Zhang¹, Liming Liu¹, Yufei Yang¹, Yu Sun¹, Jiaxu Ning², Yu Zhang³, Changsheng Zhang^1,4,*, Ying Guo⁴

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5201-5223, 2024, DOI:10.32604/cmc.2024.050863 - 20 June 2024

Abstract The flying foxes optimization (FFO) algorithm, as a newly introduced metaheuristic algorithm, is inspired by the survival tactics of flying foxes in heat wave environments. FFO preferentially selects the best-performing individuals. This tendency will cause the newly generated solution to remain closely tied to the candidate optimal in the search area. To address this issue, the paper introduces an opposition-based learning-based search mechanism for FFO algorithm (IFFO). Firstly, this paper introduces niching techniques to improve the survival list method, which not only focuses on the adaptability of individuals but also considers the population’s crowding degree More >

Leila Safari-Monjeghtapeh¹, Mansour Esmaeilpour^2,*

Computer Systems Science and Engineering, Vol.48, No.3, pp. 705-721, 2024, DOI:10.32604/csse.2024.044892 - 20 May 2024

Abstract Path-based clustering algorithms typically generate clusters by optimizing a benchmark function. Most optimization methods in clustering algorithms often offer solutions close to the general optimal value. This study achieves the global optimum value for the criterion function in a shorter time using the minimax distance, Maximum Spanning Tree “MST”, and meta-heuristic algorithms, including Genetic Algorithm “GA” and Particle Swarm Optimization “PSO”. The Fast Path-based Clustering “FPC” algorithm proposed in this paper can find cluster centers correctly in most datasets and quickly perform clustering operations. The FPC does this operation using MST, the minimax distance, and… More >

Fangzhen Ge^1,3, Yating Wu^1,*, Debao Chen^2,4, Longfeng Shen^1,5

Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 189-211, 2024, DOI:10.32604/iasc.2024.042841 - 21 May 2024

Abstract It is still a huge challenge for traditional Pareto-dominated many-objective optimization algorithms to solve many-objective optimization problems because these algorithms hardly maintain the balance between convergence and diversity and can only find a group of solutions focused on a small area on the Pareto front, resulting in poor performance of those algorithms. For this reason, we propose a reference vector-assisted algorithm with an adaptive niche dominance relation, for short MaOEA-AR. The new dominance relation forms a niche based on the angle between candidate solutions. By comparing these solutions, the solution with the best convergence is More >