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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 · 5,705 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 · 5,235 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleGlobal Supply Chain: Enhance Production Cost Efficiency Through Machine LearningLoubna Moumeni, Mohammed SaberMachine learning has enabled the discovery of various disciplines and patterns in Supply Chain Management (SCM). The entire industrial sector is striving to harness the contextual intelligence provided by machine learning by exploring new areas within the supply chain network. This article delves into Supply Chain Management (SCM) and its broader implications beyond logistics. SCM involves the resources, methods, and … …Journal of Computer Science, Vol. 20, Issue 9 · 14 Jun 2024 · 5,320 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDefect Classification of Reinforced Concrete Structures with Nondestructive Tests Using Statistical and Machine Learning MethodsSajjad Sayyar-Roudsari, Armaghan Shalbaftabar, Farshid Damirchilo et al.In this study, twelve reinforced concrete beams were constructed, each with specified dimensions and initial compressive strength. The beams were divided into four groups: A control group without any defect, a void group featuring a centrally located void, a corrosion group and a debonding group. The impact echo test was used for nondestructive testing, gathering data on compressive and shear … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 3 · 11 Jun 2024 · 5,264 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Multi-Split Cross-Strategy for Enhancing Machine Learning Algorithms Prediction Results with Data Generated by Conditional Generative Adversarial NetworkAbdelfattah Abassi, Brahim Bakkas et al.In this study, we present a Multi-Split Cross-Strategy (MSC-Strategy) designed to leverage synthetic tabular data generated by a Conditional Generative Adversarial Network (CGAN). Our study aims to investigate the potential of synthetic data in comparison to real-world data for improving machine learning predictive results. Firstly, we develop a CGAN architecture tailored to generate synthetic tabular data, trained on a comprehensive … …Journal of Computer Science, Vol. 20, Issue 7 · 9 Apr 2024 · 6,701 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleHuman Activity Prediction Studies Using Wearable Sensors and Machine LearningDivya Sharma, Usha ChauhanNowadays, Human Activity Recognition (HAR) systems have become so demanding that they find applications in the field of assisted living systems, elderly healthcare systems, smart homes, healthcare monitoring applications, surveillance systems, etc. Due to its increasing demand in computer science; machine learning and deep learning have brought a paradigm shift in the area of sensor-based recognition systems. Providing accurate information … …Journal of Computer Science, Vol. 20, Issue 4 · 14 Feb 2024 · 7,211 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFuel Prediction Model for Driving Patterns Using Machine Learning TechniquesManjunath TK, Ashok Kumar PSIn recent years, the demand for fuel efficiency has become a crucial aspect of the automotive industry. Predicting fuel economy accurately is essential for optimizing vehicle performance and reducing environmental impact. This proposed model presents a machine learning-based approach for developing a fuel prediction model using the real dataset. The model aims to predict fuel efficiency for different drivers by … …Journal of Computer Science, Vol. 20, Issue 3 · 29 Jan 2024 · 5,488 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 · 7,047 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 · 8,738 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA New Algorithm for Earthquake Prediction Using Machine Learning MethodsNada Badr Jarah, Abbas Hanon Hassin Alasadi, Kadhim Mahdi HashimSeismic tremors are among the foremost perilous normal fiascos individuals confront due to their event without earlier caution and their effect on their lives and properties. In expansion, to consider future disaster prevention measures for major earthquakes, it is necessary to predict earthquakes using Neural Networks (NN). A machine learning technique has developed a technology to predict earthquakes from ground … …Journal of Computer Science, Vol. 20, Issue 2 · 23 Dec 2023 · 7,087 accessesView PDFCite