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480 results for “Machine Learning (ML)”

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Research ArticleOpen accessEvery word in the titleComparative Analysis on Prediction of Chronic KidneyDisease by various Machine Learning ModelsNikhil Verma, Tripti Sharma, Bobbinpreet Kaur, Ayush DograChronic Kidney Disease (CKD) is a prevalent global healthconcern, which is affecting a number of people in the whole world. Earlydetection & precise checking of CKD are really important for essentialsupervision & intervention to prevent disease progression and associatedcomplications. Machine learning (ML) models have emerged as favourabletools for CKD detection due to their ability to analyse complex data patternsand provide … …Journal of Computer Science, Vol. 21, Issue 6 · 24 May 2025 · 5,939 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleDDoS Mitigation Using Machine Learning in Software-Defined NetworksAhmed Gaber Abu Abd-Allah, Noureldin Omar Mohamed, Mohamed Samir Mohamed et al.With the escalating frequency and sophistication of Distributed Denial of Service (DDoS) attacks, the realm of cyber security has witnessed a paradigm shift towards innovative solutions. This review explores the potential of machine learning as a powerful defense mechanism in the field of DDoS mitigation within Software-Defined Networks (SDNs). The study methodically examines a variety of machine learning algorithms used … …Journal of Computer Science, Vol. 21, Issue 4 · 23 Mar 2025 · 6,774 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Comprehensive Survey on Fake News Detection Using Machine LearningShraddha Shah, Sachin PatelIn the age of information data surplus and social media impact, the propagation of fake news has developed a significant societal concern. This challenge requires robust tools and methodologies for addressing, with machine learning emerging as a promising approach. The paper reviews different machine learning techniques in fake news detection, including supervised, unsupervised and semi-supervised methods. Supervised methods utilize labelled … …Journal of Computer Science, Vol. 21, Issue 4 · 20 Mar 2025 · 9,212 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleBeatbox Classification to Distinguish User Experiences Using Machine Learning ApproachesJason Martanto, Iman Herwidiana KartowisastroResearch regarding beatbox classification has generated a relatively significant growth in the past decade. Although the differences between contributors’ expertise within a vocal percussion dataset have been mentioned in previous works, the impact of those discrepancies has not been thoroughly investigated. In this study, the authors explore performances of machine learning algorithms for beatbox classification, with an emphasis on prior … …Journal of Computer Science, Vol. 21, Issue 4 · 18 Mar 2025 · 5,208 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEnhancing Telecommunication Network Management with Autonomous Optimization Agents and Machine LearningDanny Adil Sibarani, Evaristus Didik MadyatmadjaThis study explores the integration of Machine Learning (ML) and Autonomous Optimization Agents (AOAs) in the management and optimization of Radio Access Networks (RAN). The research addresses the growing challenges posed by the need for skilled network experts capable of managing and analyzing large-scale network data, including Key Performance Indicators (KPIs) and thousands of network configuration parameters. To overcome these … …Journal of Computer Science, Vol. 21, Issue 2 · 4 Mar 2025 · 7,041 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleMachine Learning-Based Traffic Prediction in 4G LTE Networks. Case Study of a Mobile Operator in CameroonEric Michel Deussom Djomadji, Valery Nkemeni et al.Mobile subscribers are increasingly demanding the availability of broadband services while the radio resources allowing them to be connected are limited. Understanding mobile Internet consumption trends and subscriber traffic demands is essential to enable the management of existing radio resources. However, it can be difficult to understand and describe the data usage patterns of mobile users because of the complexity … …American Journal of Engineering and Applied Sciences, Vol. 18, Issue 1 · 1 Mar 2025 · 8,728 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleThe Optimized Extreme Learning Machine (GA-OELM) for DDoS Attack Detection in Cloud EnvironmentMeryem Ec-Sabery, Adil Ben Abbou, Abdelali Boushaba et al.The widespread adoption of cloud computing has increased the attack surface and raised significant security concerns. A Distributed Denial of Service (DDoS) is a serious attack that depletes the network and server resources in cloud computing, causing service downtime or reduced performance. Therefore, defending against DDoS attacks becomes an urgent need. In this present paper, we propose an Optimized Extreme … …Journal of Computer Science, Vol. 21, Issue 1 · 19 Dec 2024 · 5,033 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleMulti-Source Cyber Intrusion Detection Using Ensemble Machine LearningTaskeen Ali Khan, Sara Abbas, Biswaranjan Senapati et al.The increased usage of digital technologies across businesses has led to an increase in cybercrime. It is difficult for existing intrusion detection systems to detect highly skilled hacking attempts; however, machine learning has been suggested as a way around these drawbacks. The purpose of this study is to evaluate how well various machine learning algorithms identify and stop cyberattacks in … …Journal of Computer Science, Vol. 21, Issue 1 · 14 Dec 2024 · 5,696 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Novel Optimized Machine Learning Approach for Early Prediction of Heart Disease Using Bio-Inspired AlgorithmsIndira Priyadarsini, I.S. Siva Rao, P. Swetha et al.This study presents a novel approach for early prediction of heart disease using bio-inspired optimization algorithms to select and optimize features. The proposed approach utilizes a Genetic Algorithm (GA), Bat Algorithm (BA), Bee Algorithm (BA), and Ant Colony Optimization (ACO) to optimize a set of four features for improved prediction accuracy. The optimization process aims to identify the most relevant … …Journal of Computer Science, Vol. 21, Issue 1 · 4 Dec 2024 · 5,227 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleEconomic Theory and Machine Learning Integration in Asset Pricing and Portfolio Optimization: A Bibliometric Analysis and Conceptual FrameworkPatrick Kevin Aritonang, Sudarso Kaderi Wiryono, Taufik FaturohmanThe integration of Machine Learning (ML) with economic theory has transformed financial market analysis, particularly in asset pricing and portfolio optimization. This study synthesizes existing research, identifies gaps and elucidates ML's impact on enhancing economic models and strategies through a Systematic Literature Review (SLR) of 401 relevant documents using bibliometric methodology and VOS viewer. Results show an increasing trend in … …Journal of Computer Science, Vol. 20, Issue 10 · 7 Aug 2024 · 5,715 accessesView PDFCite