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158 results for “Predictive Model”
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Research ArticleOpen accessIn the abstractRandom Forest and Extreme Gradient Boosting with Bayesian Hyperparameter Optimization for Landslide Susceptibility Mapping in Penang Island, MalaysiaDorothy Anak Martin Atok, Soo See Chai, Kok Luong Goh et al.Landslide susceptibility models often face challenges of overfitting and overestimation. This research focuses on improving the predictive capabilities of the Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms by applying Bayesian Hyperparameter Optimization (BayesOpt). Penang Island, a region in Malaysia prone to frequent landslides, was chosen as the study area. Ten Landslide Conditioning Factors (LCFs), including elevation, slope angle, … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 3,103 accessesView PDFCite
Research ArticleOpen accessIn the abstractSelf-Supervised Contrastive Learning for Steering Angle Prediction in Autonomous Driving SimulationsMaxson Phang, Suryadiputra LiawatimenaPredicting steering angles is a crucial task in autonomous driving, with end-to-end deep learning being a widely used approach. However, such models often suffer from overfitting to learned trajectories, limiting their generalization to new data. To address this, self-supervised contrastive learning is explored as an alternative, allowing models to learn meaningful representations without labeled data. The primary objective is to … …Journal of Computer Science, Vol. 21, Issue 9 · 20 Oct 2025 · 2,581 accessesView PDFCite
Research ArticleOpen accessIn the abstractEarly Diagnosis of Parkinson's Disease Through Voice Analysis and Machine LearningAmrita Naik, Mohd Sahil Khan, Akhilesh Manoj Saraf et al.Parkinson’s Disease (PD) is a progressive neurological disorder, and its prevalence has increased considerably in recent years. Early and accurate diagnosis plays a crucial role in effective treatment, but identifying the disease in its early stages remains challenging, especially for non-specialist clinicians. This study presents a predictive analytics framework for detecting Parkinson's disease using voice-based features. To improve the diversity … …Journal of Computer Science, Vol. 22, Issue 11 · 9 Oct 2026 · 637 accessesView PDFCite
Research ArticleOpen accessIn the abstractExplainable MedAttn-ResNet50 for Automated Kidney Tumor Classification from CT Images With Grad-CAM VisualizationD. Vetrithangam, Pramod Kumar, Shilpasree S. et al.Kidney tumor classification from CT imaging remains challenging due to CT-specific intensity variations, tumor heterogeneity, and limited clinically meaningful interpretability in existing deep learning models. To address these limitations, we propose an Explainable MedAttn-ResNet50 framework that integrates radiology-driven preprocessing, multi-scale feature extraction, and medical attention mechanisms within a unified architecture. The preprocessing pipeline applies radiology-inspired intensity normalization, contrast enhancement, and … …Journal of Computer Science, Vol. 22, Issue 8 · 13 Aug 2026 · 1,120 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnchoring Public Health Forecasts: High-Precision Obesity Prevalence Estimation Via Hybrid Geodemographic Ensemble RegressionTrenton Ward, Isaac OsunmakindeObesity remains a major driver of chronic disease and rising healthcare costs in the United States. Yet, most existing predictive models rely on single-model classifiers and rarely incorporate spatial structure or ensemble-based regression, thereby limiting their ability to capture geodemographic variation. This study introduces a hybrid unsupervised–supervised ensemble framework that integrates K-Means spatial profiling with a Stacking Regressor to address … …Journal of Computer Science, Vol. 22, Issue 7 · 31 Jul 2026 · 632 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Integrated Machine Learning Framework for Citrus Grading and Yield Prediction Using Classifier-Informed RegressionLydia Dede Obeng, Isaac O. OsunmakindeAgriculture remains a cornerstone of human sustenance, yet accurate citrus fruit grading and yield predictions remain significant challenges due to visual similarities between varieties such as oranges and grapefruits. This includes the inefficiencies of manual grading. This study presents a new dual-function machine learning system that integrates classification and regression to simultaneously grade citrus fruits and forecast crop yields. This … …Journal of Computer Science, Vol. 22, Issue 4 · 24 Apr 2026 · 1,891 accessesView PDFCite
Research ArticleOpen accessIn the abstractDevelopment of a Machine Learning Based Mobile and Web Crop Recommendation System for Precision Farming in WardhaAishwarya Kadu, KTV ReddyAgricultural productivity is crucial for economic growth of a nation, especially for countries like India which is highly dependent on agriculture. This study addresses the need for cutting-edge technology to enhance crop productivity by proposing a Mobile/Web-based precision farming system. Leveraging Machine Learning (ML) algorithms, the proposed system recommends optimal crops based on several factors such as environmental parameters (Nitrogen … …Journal of Computer Science, Vol. 22, Issue 3 · 20 Mar 2026 · 1,660 accessesView PDFCite
Research ArticleOpen accessIn the abstractCuckoo Search Optimized Random Forest for Breast Cancer PrognosisPrasad S. Sase, Debabrata Swain, Shailesh KumarBreast cancer remains a major global health concern due to its high mortality rate, particularly when diagnosis occurs at an advanced stage. Accurate and early differentiation between benign and malignant tumors is therefore critical for improving patient outcomes. Conventional diagnostic practices largely depend on manual assessment and clinical expertise, which may lead to subjective variability in decision-making. To overcome this … …Journal of Computer Science, Vol. 22, Issue 1 · 31 Jan 2026 · 2,098 accessesView PDFCite
Research ArticleOpen accessIn the abstractSoft Marking Scheme of SVM Hierarchical Classifiers for Attack ClassificationAzizi Abdullah, Warhamni Jani@MokhtarClassification is a predictive modelling problem that involves assigning a class label to an instance correctly. There exist several strategies in machine learning to deal with the multi-class classification problems for attack detection. One of the popular strategies is the one-vs-one that decomposes the multi-class problem into multiple binary ones. The approach has been applied in many popular supervised learning … …Journal of Computer Science, Vol. 17, Issue 9 · 27 Sep 2021 · 6,000 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting the Remaining Lifetime of Distribution Transformers using Machine LearningNtiminity Abontakoyah Enoch, Puguo Gbene George, Justice AningDistribution Transformer is a crucial element in deciding the power flow in large power systems. Their better performance implies high power system efficiency and enhanced power transfer capability. However, various Distribution Transformer failures in the recent past lead to power supply disturbance and have acquired much attention from the electrical intellectuals. It is of considerable significance to accurately get the … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 4 · 1 Jan 2021 · 6,644 accessesView PDFCite