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29 articles for “Predictive Modeling”
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Research ArticleOpen accessPhrase in the title3D Mesh Streaming based on Predictive ModelingV. Vani, R. Pradeep Kumar, S. MohanThe complexity in 3D virtual environment over the web is growing rapidly every day. This 3D virtual environment comprises a set of structured scenes and each scene has multiple 3D objects/meshes. Therefore the granular level of the block in a virtual environment is the object. In a virtual environment, it is required to give user interactions for every 3D object … …Journal of Computer Science, Vol. 8, Issue 7 · 7 Jun 2012 · 7,410 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAnalyzing Temperature-Dependent Thermal Properties of Titanium Aluminide Using ANN Predictive ModelingArmaghan Shalbaftabar, Kristen Rhinehardt, Dhananjay KumarThis study presents a comprehensive analysis of the thermal behavior of Titanium Aluminide (TiAl) across a range of temperatures using an Artificial Neural Network (ANN) predictive model. The study investigates various material properties of TiAl, including Band Gap, Young Module, Density, Energy Absorption, Thermal Conductivity, and Specific Heat, at different temperature points. The ANN model accurately captures the temperature-dependent trends … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 4 · 20 Nov 2024 · 4,308 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePredictive Modeling Applied to Structured Clinical Data Extracted from Electronic Health Records: An Architectural Hypothesis and A First ExperimentAlessandra Pieroni, Alessandro Cabroni, Francesca Fallucchi, Noemi ScarpatoPredictive analysis is one of current important issues in the healthcare context. A lot of patients’ input data can be obtained from their Electronic Health Records. In our research, we propose a general architecture named Health Prediction Architecture. Initially, we consider that data refer to strongly structured health datasets (no free text). Our objectives are related to exploring some problems … …Journal of Computer Science, Vol. 17, Issue 9 · 7 Sep 2021 · 6,571 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePredictive Mathematical Modeling and Classification of Retail Sales Orders Using AI Machine Learning TechniquesMohammad Subhi Al-Batah, Mowafaq Salem Alzboon, Hamzeh ZureigatThis study presents a systematic mathematical model known as a low-code approach to classifying retail sales orders by size using AI machine learning techniques within the Orange Data Mining platform. Leveraging a real-world sales dataset sourced from Kaggle, we implemented and evaluated ten classification models, including ensemble learners (AdaBoost, Gradient Boosting), probabilistic classifiers (Naïve Bayes), distance-based methods (kNN), and interpretable … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 1,567 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAdvancements In Precision Agriculture: A Review on Image-Based Stress Detection and Predictive Yield Loss ModelingA. Josephine, A. SubhashiniPrecision agriculture utilizes cutting-edge technologies to maximize the management of crops, enhance utilization of resources, and maximize yield forecasting. This study critically analyzes 53 peer-reviewed articles to evaluate advancements in image-based stress detection and yield prediction techniques for precision agriculture. The review enumerates main issues, such as image-based analysis methods, different crop stress aspects (biotic, environmental, and abiotic), and remote … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Dec 2025 · 2,508 accessesView PDFCite
Research ArticleOpen accessIn the keywordsUMPM-Net: A Multimodal Deep Learning Framework for Colorectal Cancer PrognosisK. Muthuchamy, S K. Piramu PreethikaColorectal cancer (CRC) is one of the most common cancers worldwide, for which early prediction of patient outcomes is important for personalised treatment planning and to improve survival. However, current prediction systems are limited in the fact that they are based on single-modality data and cannot capture the complex interactions between clinical, imaging, and genomic factors. To overcome these shortcomings, … …Journal of Computer Science, Vol. 22, Issue 9 · 20 Sep 2026 · 613 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIdentification of Cancer: Mesothelioma’s Disease Using Logistic Regression and Association RuleAvishek ChoudhuryMalignant Pleural Mesothelioma (MPM) or malignant mesothelioma (MM) is an atypical, aggressive tumor that matures into cancer in the pleura, a stratum of tissue bordering the lungs. Diagnosis of MPM is difficult and it accounts for about seventy-five percent of all mesothelioma diagnosed yearly in the United States of America. Being a fatal disease, early identification of MPM is crucial … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 4 · 7 Dec 2018 · 7,224 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHABITAT SUITABILITY MODELING FOR EXPLORATION OF THE SPATIAL DISTRIBUTION OF KASHMIR MUSK DEER IN DACHIGAM NATIONAL PARK, KASHMIRMudasir AliMusk deer are highly important as a medicinal species that are severely exploited throughout their range of occurrence due to the medicinal value of the musk produced only by the male individuals. Methods used for studying the populations and distributions of other ungulates do not work well with musk deer and the presence of a unified methodology for studying musk … …American Journal of Environmental Sciences, Vol. 10, Issue 5 · 20 Aug 2014 · 7,861 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Comparative Study of Resampling, Cost-Sensitive, and Ensemble Techniques for Handling Class Imbalance in Indonesian Financial DataGunawan Kurnia, Ditdit Nugeraha UtamaHandling class imbalance is a critical challenge in machine learning applications, particularly in financial domains where minority instances often represent significant anomalies such as fraud or audit risks. Various oversampling and undersampling methods were tested, alongside cost-sensitive adjustments and ensemble models including Random Forest, AdaBoost, Gradient Boosting, and XGBoost. The evaluation, based on 10-fold stratified cross-validation and performance metrics such … …Journal of Computer Science, Vol. 22, Issue 2 · 27 Feb 2026 · 1,874 accessesView PDFCite
Research ArticleOpen accessIn the keywordsINCORPORATING PRIOR KNOWLEDGE INTO TEMPORAL DIFFERENCE NETWORKSBritton Wolfe, James HarpeDeveloping general purpose algorithms for learning an accurate model of dynamical systems from example traces of the system is still a challenging research problem. Predictive State Representation (PSR) models represent the state of a dynamical system as a set of predictions about future events. Our work focuses on improving Temporal Difference Networks (TD Nets), a general class of predictive state … …Journal of Computer Science, Vol. 10, Issue 11 · 18 Dec 2014 · 7,837 accessesView PDFCite