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176 results for “Machine Learning Models”
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Research ArticleOpen accessIn the abstractImproving Diabetes Risk Prediction Using Ensemble Boosting and SMOTE-Based Class BalancingKittipol Wisaeng, Pankom Sriboonlue, Benchalak MuangmeesriAccurate diabetes prediction is vital for early intervention, optimized resource allocation, and minimizing long-term complications. This study presents a comparative evaluation of traditional and advanced machine learning models for diabetes classification using a structured clinical dataset. Seven baseline algorithms were assessed against five advanced ensemble methods: CatBoost, LightGBM, XGBoost, Voting Ensemble, and Stacking Ensemble. To improve algorithm learning, the Synthetic … …Journal of Computer Science, Vol. 22, Issue 1 · 1 Feb 2026 · 1,984 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementing a Hybrid Parallel Framework Utilizing Machine and Deep Learning for Rapid Rumor Detection in Social MediaNeetu Rani, Amit Kumar Bhardwaj, Shaily Jain et al.Numerous businesses have faced significant repercussions due to the widespread dissemination of false information and rumors across social media platforms. The impact of fake news extends to tarnishing public perception, damaging corporate reputations, disrupting communities, undermining governmental integrity, exposing companies to risks, and posing a grave threat to social cohesion. This research article delves into the endeavours of prominent researchers … …Journal of Computer Science, Vol. 21, Issue 12 · 27 Jan 2026 · 1,819 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancements 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 · 2,520 accessesView PDFCite
Research ArticleOpen accessIn the abstractInternet of Things and Human Neocortex Inspired Algorithms for the Plant Disease Prediction-Sheath Blight for Paddy PlantThangaraj Ethilu, K. Parthiban, Arockia Jayadhas S et al.Sheath blight disease (Rhizoctonia solani) poses a critical threat to paddy (Oryza sativa) production, causing up to 50% yield losses under conducive environmental conditions. Existing computer vision-based disease detection systems identify infections only after symptom manifestation, while conventional machine learning prediction models suffer from high computational demands, data preprocessing requirements, and noise sensitivity. This research proposes a novel Hierarchical Temporal … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 1,780 accessesView PDFCite
Research ArticleOpen accessIn the abstractFedCarepod: Federated Quantum Transfer Learning Approach in Screening Process for Early Detection of Liver AbnormalitiesK MalaThe liver is the most frequently injured intra-abdominal organ that leads to complications. Visual interpretation depends on the expertise, and this justifies the need for automatic accelerated assistive prediction system. Classical and Quantum machine learning approaches are combined to leverage their benefits, and the feasibility of designing a novel system is explored. This approach successfully ends up with health care … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 2,076 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Deep Learning Approach for Telugu Domain Identification with Multichannel LSTM-CNNBuddha Hari Kumar, Chitra Perumal, Inakoti Ramesh Raja et al.The vast growth of textual data has ushered into the limelight, a plethora of applications in information retrieval and natural language processing (NLP). Proper extraction of information from text is heavily dependent on recognizing the thematic content, which becomes crucial in the tasks of document summarization, information extraction, question answering, machine translation, and sentiment analysis. The great complexity of this … …Journal of Computer Science, Vol. 21, Issue 9 · 26 Nov 2025 · 2,400 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploratory Data Analysis of Applications of Encryption for Netflix by ML ModelsAnanth Maria Pushpa, Subramanian ShanmugamThis study examines the performance of various machine learning algorithms in analyzing Netflix's dataset, with a focus on encryption methods used for data protection. We evaluated several models including Ada BoostM1, IBk, Random Forest, and Decision Stump using multiple performance metrics. This work analysis revealed that the Ada BoostM1 model achieved the highest accuracy at 97.14%, outperforming other algorithms. It … …Journal of Computer Science, Vol. 21, Issue 9 · 24 Nov 2025 · 1,930 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Financial Statement Failure of Listed Firms in Market for Alternative Investment (mai) using Machine LearningPattanapong Kumsin, Salakjit Ninlaphay, Anupong SukprasertThe purpose of this research is to investigate the financial ratios of companies listed on the Market for Alternative Investment (mai) in Thailand, as well as the likelihood of these companies' financial statement failure. It also intends to create a financial statement failure predicting model for companies listed on the mai and assess the performance of various forecasting models using … …Journal of Computer Science, Vol. 21, Issue 9 · 24 Nov 2025 · 2,243 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Cybersecurity: Dynamically Retrainable Firewalls for Real-Time Network ProtectionSina AhmadiThe growing complexity of cyberattacks has necessitated the evolution of firewall technologies from static models to adaptive, machine learning-driven systems. This research introduces “Dynamically Retrainable Firewalls”, which respond to emerging threats in real-time. Unlike traditional firewalls that rely on static rules to inspect traffic, these advanced systems leverage machine learning algorithms to analyze network traffic patterns dynamically and identify threats. … …Journal of Computer Science, Vol. 21, Issue 9 · 7 Nov 2025 · 2,562 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnimal Health Prediction Using Hybrid KNN Based Vector Neighbor Classification Model: A Machine Learning ApproachJ. Rathi, A. SumathiAnimal condition disease prediction is a crucial task in veterinary medicine, and accurate prediction can significantly improve animal health and reduce economic losses. This paper proposed a novel hybrid classification model that combines an Improved Fuzzy-based feature selection process with a Hybrid KNN-based Vector Neighbor Classification model to enhance animal condition disease prediction. The proposed model aims to improve the … …Journal of Computer Science, Vol. 21, Issue 9 · 21 Oct 2025 · 2,905 accessesView PDFCite