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  • Open Access

    ARTICLE

    Robust Particle Swarm Optimization Algorithm for Modeling the Effect of Oxides Thermal Properties on AMIG 304L Stainless Steel Welds

    Rachid Djoudjou1,*, Abdeljlil Chihaoui Hedhibi3, Kamel Touileb1, Abousoufiane Ouis1, Sahbi Boubaker2, Hani Said Abdo4,5

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1809-1825, 2024, DOI:10.32604/cmes.2024.053621 - 27 September 2024

    Abstract There are several advantages to the MIG (Metal Inert Gas) process, which explains its increased use in various welding sectors, such as automotive, marine, and construction. A variant of the MIG process, where the same equipment is employed except for the deposition of a thin layer of flux before the welding operation, is the AMIG (Activated Metal Inert Gas) technique. This study focuses on investigating the impact of physical properties of individual metallic oxide fluxes for 304L stainless steel welding joint morphology and to what extent it can help determine a relationship among weld depth… More >

  • Open Access

    ARTICLE

    Far and Near Optimization: A New Simple and Effective Metaphor-Less Optimization Algorithm for Solving Engineering Applications

    Tareq Hamadneh1,2, Khalid Kaabneh3, Omar Alssayed4, Kei Eguchi5,*, Zeinab Monrazeri6, Mohammad Dehghani6

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1725-1808, 2024, DOI:10.32604/cmes.2024.053236 - 27 September 2024

    Abstract In this article, a novel metaheuristic technique named Far and Near Optimization (FNO) is introduced, offering versatile applications across various scientific domains for optimization tasks. The core concept behind FNO lies in integrating global and local search methodologies to update the algorithm population within the problem-solving space based on moving each member to the farthest and nearest member to itself. The paper delineates the theory of FNO, presenting a mathematical model in two phases: (i) exploration based on the simulation of the movement of a population member towards the farthest member from itself and (ii)… More >

  • Open Access

    ARTICLE

    Research on Feature Matching Optimization Algorithm for Automotive Panoramic Surround View System

    Guangbing Xiao*, Ruijie Gu, Ning Sun, Yong Zhang

    Computer Systems Science and Engineering, Vol.48, No.5, pp. 1329-1348, 2024, DOI:10.32604/csse.2024.050817 - 13 September 2024

    Abstract In response to the challenges posed by insufficient real-time performance and suboptimal matching accuracy of traditional feature matching algorithms within automotive panoramic surround view systems, this paper has proposed a high-performance dimension reduction parallel matching algorithm that integrates Principal Component Analysis (PCA) and Dual-Heap Filtering (DHF). The algorithm employs PCA to map the feature points into the lower-dimensional space and employs the square of Euclidean distance for feature matching, which significantly reduces computational complexity. To ensure the accuracy of feature matching, the algorithm utilizes Dual-Heap Filtering to filter and refine matched point pairs. To further More >

  • Open Access

    ARTICLE

    Cyberbullying Sexism Harassment Identification by Metaheurustics-Tuned eXtreme Gradient Boosting

    Milos Dobrojevic1,4, Luka Jovanovic1, Lepa Babic3, Miroslav Cajic5, Tamara Zivkovic6, Miodrag Zivkovic2, Suresh Muthusamy7, Milos Antonijevic2, Nebojsa Bacanin2,4,8,9,*

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4997-5027, 2024, DOI:10.32604/cmc.2024.054459 - 12 September 2024

    Abstract Cyberbullying is a form of harassment or bullying that takes place online or through digital devices like smartphones, computers, or tablets. It can occur through various channels, such as social media, text messages, online forums, or gaming platforms. Cyberbullying involves using technology to intentionally harm, harass, or intimidate others and may take different forms, including exclusion, doxing, impersonation, harassment, and cyberstalking. Unfortunately, due to the rapid growth of malicious internet users, this social phenomenon is becoming more frequent, and there is a huge need to address this issue. Therefore, the main goal of the research… More >

  • Open Access

    ARTICLE

    Internet of Things Enabled DDoS Attack Detection Using Pigeon Inspired Optimization Algorithm with Deep Learning Approach

    Turki Ali Alghamdi, Saud S. Alotaibi*

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4047-4064, 2024, DOI:10.32604/cmc.2024.052796 - 12 September 2024

    Abstract Internet of Things (IoTs) provides better solutions in various fields, namely healthcare, smart transportation, home, etc. Recognizing Denial of Service (DoS) outbreaks in IoT platforms is significant in certifying the accessibility and integrity of IoT systems. Deep learning (DL) models outperform in detecting complex, non-linear relationships, allowing them to effectually severe slight deviations from normal IoT activities that may designate a DoS outbreak. The uninterrupted observation and real-time detection actions of DL participate in accurate and rapid detection, permitting proactive reduction events to be executed, hence securing the IoT network’s safety and functionality. Subsequently, this… More >

  • Open Access

    ARTICLE

    Optimized Phishing Detection with Recurrent Neural Network and Whale Optimizer Algorithm

    Brij Bhooshan Gupta1,2,3,*, Akshat Gaurav4, Razaz Waheeb Attar5, Varsha Arya6,7, Ahmed Alhomoud8, Kwok Tai Chui9

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4895-4916, 2024, DOI:10.32604/cmc.2024.050815 - 12 September 2024

    Abstract Phishing attacks present a persistent and evolving threat in the cybersecurity land-scape, necessitating the development of more sophisticated detection methods. Traditional machine learning approaches to phishing detection have relied heavily on feature engineering and have often fallen short in adapting to the dynamically changing patterns of phishing Uniform Resource Locator (URLs). Addressing these challenge, we introduce a framework that integrates the sequential data processing strengths of a Recurrent Neural Network (RNN) with the hyperparameter optimization prowess of the Whale Optimization Algorithm (WOA). Our model capitalizes on an extensive Kaggle dataset, featuring over 11,000 URLs, each More >

  • Open Access

    ARTICLE

    Multi-Objective Optimization of Multi-Product Parallel Disassembly Line Balancing Problem Considering Multi-Skilled Workers Using a Discrete Chemical Reaction Optimization Algorithm

    Xiwang Guo1, Liangbo Zhou1, Zhiwei Zhang1,*, Liang Qi2,*, Jiacun Wang3, Shujin Qin4, Jinrui Cao5

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4475-4496, 2024, DOI:10.32604/cmc.2024.048123 - 12 September 2024

    Abstract This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers. A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle time. Based on a product’s AND/OR graph, matrices for task-skill, worker-skill, precedence relationships, and disassembly correlations are developed. A multi-objective discrete chemical reaction optimization algorithm is designed. To enhance solution diversity, improvements are made to four reactions: decomposition, synthesis, intermolecular ineffective collision, and wall invalid collision reaction, completing the evolution of molecular individuals. The established model and improved algorithm are applied to ball More >

  • Open Access

    ARTICLE

    Chase, Pounce, and Escape Optimization Algorithm

    Adel Sabry Eesa*

    Intelligent Automation & Soft Computing, Vol.39, No.4, pp. 697-723, 2024, DOI:10.32604/iasc.2024.053192 - 06 September 2024

    Abstract While many metaheuristic optimization algorithms strive to address optimization challenges, they often grapple with the delicate balance between exploration and exploitation, leading to issues such as premature convergence, sensitivity to parameter settings, and difficulty in maintaining population diversity. In response to these challenges, this study introduces the Chase, Pounce, and Escape (CPE) algorithm, drawing inspiration from predator-prey dynamics. Unlike traditional optimization approaches, the CPE algorithm divides the population into two groups, each independently exploring the search space to efficiently navigate complex problem domains and avoid local optima. By incorporating a unique search mechanism that integrates More >

  • Open Access

    ARTICLE

    Bio-Inspired Intelligent Routing in WSN: Integrating Mayfly Optimization and Enhanced Ant Colony Optimization for Energy-Efficient Cluster Formation and Maintenance

    V. G. Saranya*, S. Karthik

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 127-150, 2024, DOI:10.32604/cmes.2024.053825 - 20 August 2024

    Abstract Wireless Sensor Networks (WSNs) are a collection of sensor nodes distributed in space and connected through wireless communication. The sensor nodes gather and store data about the real world around them. However, the nodes that are dependent on batteries will ultimately suffer an energy loss with time, which affects the lifetime of the network. This research proposes to achieve its primary goal by reducing energy consumption and increasing the network’s lifetime and stability. The present technique employs the hybrid Mayfly Optimization Algorithm-Enhanced Ant Colony Optimization (MFOA-EACO), where the Mayfly Optimization Algorithm (MFOA) is used to… More >

  • Open Access

    ARTICLE

    A Microseismic Signal Denoising Algorithm Combining VMD and Wavelet Threshold Denoising Optimized by BWOA

    Dijun Rao1,2,3,4, Min Huang1,2,3,5, Xiuzhi Shi4, Zhi Yu6,*, Zhengxiang He7

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 187-217, 2024, DOI:10.32604/cmes.2024.051402 - 20 August 2024

    Abstract The denoising of microseismic signals is a prerequisite for subsequent analysis and research. In this research, a new microseismic signal denoising algorithm called the Black Widow Optimization Algorithm (BWOA) optimized Variational Mode Decomposition (VMD) joint Wavelet Threshold Denoising (WTD) algorithm (BVW) is proposed. The BVW algorithm integrates VMD and WTD, both of which are optimized by BWOA. Specifically, this algorithm utilizes VMD to decompose the microseismic signal to be denoised into several Band-Limited Intrinsic Mode Functions (BLIMFs). Subsequently, these BLIMFs whose correlation coefficients with the microseismic signal to be denoised are higher than a threshold… More >

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