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97 results for “Predict Learning”
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Research ArticleOpen accessIn the abstractDengue Fever Prediction Empowered by Radial Basis Function Networks, Dynamic Mode Decomposition, and Learning-Based Foraging AlgorithmArchana T, Faritha Banu JDengue fever is presently considered a major health threat that must be addressed. External and internal factors that induce nonlinear oscillations in the occurrence of dengue disease have made optimal resource allocation stimulating. Public health initiatives aimed at eradicating this vector use accurate and timely data through field processes. In dengue-endemic nations, early dengue prediction remains a main concern for … …Journal of Computer Science, Vol. 22, Issue 4 · 16 Apr 2026 · 1,505 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Fleet Management with GPS Data in Port Terminals: A Deep Learning Architecture for Truck Position PredictionMohammed El Karkraoui, Hicham AttariuasEffective truck fleet management in port terminals is crucial for improving operational efficiency and reducing delays. However, GPS-based positioning systems often face limitations in port environments due to signal obstructions and network issues. This study explores the utilization of advanced methods for deep learning, particularly Recurrent Neural Networks (RNNs) for predicting truck positions when GPS signals are unavailable or unreliable. … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 2,279 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Integrated Framework to Predict the Strength of New SMILE Using Graph Attention NetworkSandhi Kranthi Reddy, S. V. G. ReddyMachine Learning (ML) and Deep Learning (DL) have significantly advanced various fields, including healthcare, finance, autonomous systems, and scientific research. In healthcare, these technologies have been widely applied to disease prediction, such as cancer and diabetes. However, the challenge of drug resistance persists, creating a need for more effective drugs. Developing new drugs is a complex, expensive, and time-intensive process, … …Journal of Computer Science, Vol. 21, Issue 10 · 25 Nov 2025 · 2,167 accessesView PDFCite
Research ArticleOpen accessIn the abstractDecoding Discrepancies: Understanding Rating and Review Gaps in Best-Selling ProductsJyoti S Verma, Jaimin N UndaviaClassification of the sentiment and using it for the rating prediction is the major task don in this paper. The emotions and opinions are expressed by the users about a product on the e-commerce website and this provides the basis for the prediction done here. The prediction of the rating enables both the user as well as the seller as … …Journal of Computer Science, Vol. 21, Issue 6 · 29 May 2025 · 5,033 accessesView PDFCite
Review ArticleOpen accessIn the abstractDeep Learning in Early Alzheimer’s Disease’s Detection: A Comprehensive Survey of Classification, Segmentation and Feature Extraction MethodsRubab Hafeez, Sadia Waheed, Syeda Aleena Naqvi et al.Alzheimer’s disease is a deadly neurological condition, impairing important memory and brain functions. Alzheimer’s disease promotes brain shrinkage, ultimately leading to dementia. Dementia diagnosis typically takes 2.8-4.4 years after the first clinical indication. Advancements in computing and information technology have led to many techniques for studying Alzheimer's disease. Early identification and therapy are crucial for preventing Alzheimer's disease, as early-onset … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,774 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine 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 accessIn the abstractAdvancing Digital Forgery Detection: A Comparative Analysis of U-Net, Buster Net, Efficient B0+ U-Net, and VGG 16+ U-Net ModelsPreeti Dhiman, Usha ChauhanForgery Detection in the area of digital images is indispensable for insuring authenticity, particularly in detecting Copy-Move, Splicing. In this research, a meticulous analysis of latest learning architectures i.e. U-Net, Buster Net, Efficient B0+U-Net and VGG16+U-Net are compared for the detecting these types of forgeries. U-Net is popular due to its potent segmentation capabilities to provide pixel-level forgery localization while … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 394 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssessing the Comparative Effectiveness of Ensemble CatBoost Versus XGBoost Models in Predicting Heart Disease OutcomesManivannan D., G. Gifta Jerith, G. Chandra Sekhar et al.Cardiovascular Diseases (CVDs) are a common form of heart disease that remains a significant global cause of mortality, responsible for more than 30% of all fatalities. Without intervention, the global fatality count is projected to reach 22 million by 2030. Arterial plaque buildup may impede blood flow, potentially causing heart attacks or strokes. A combination of risk causes, including lack … …Journal of Computer Science, Vol. 22, Issue 4 · 4 May 2026 · 1,552 accessesView PDFCite
Research ArticleOpen accessIn the abstractGradient Boosting for Heart Stroke Prediction: Investigating Unexpected Risk FactorsAniket Kailas Shahade, Priyanka V. DeshmukhHeart stroke prediction is a critical area in healthcare, aiming to identify individuals at risk and provide timely intervention. This research leverages machine learning algorithms, including Decision Tree, Random Forest, AdaBoost, and Gradient Boost, to predict the likelihood of stroke, with Gradient Boosting delivering the most accurate results. Our analysis uncovers intriguing and unexpected relationships between stroke risk and various … …Journal of Computer Science, Vol. 21, Issue 1 · 16 Dec 2024 · 4,943 accessesView PDFCite
Research ArticleOpen accessIn the abstractPhishing Website Detection Using Improved Multilayered Convolutional Neural NetworksHadia Bibi, Syed Rehan Shah, Mirza Murad Baig et al.The internet has become an essential part of many fields: Communication, entertainment, commerce, industrial production, agriculture, etc. Unfortunately, online users are vulnerable to various attacks; this could lead to financial damages and loss of personal information. Phishing is seen as an internet threat and a cybercrime where anyone can capture personal information and data by posing as a reliable source. … …Journal of Computer Science, Vol. 20, Issue 9 · 6 Jul 2024 · 6,586 accessesView PDFCite