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203 results for “Prediction Models”
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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 · 1,772 accessesView PDFCite
Research ArticleOpen accessIn the abstractOnline ML Streaming-Based Leading Ensemble Classifier for Intrusion Detection in IoTNeeraj Sharma, Neelu NihalaniIn the present decade, preventing IoT networks from malicious attacks and to ensure the privacy and integrity of data by strengthening their cybersecurity perspective is a critical concern. Traditional methods alone are not sufficient to detect multiple attacks. IDS-based system plays a crucial role to maintain security due to continuous expanding nature of IoT networks. Traditional methods alone are often … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 2,078 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 · 2,068 accessesView PDFCite
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 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 · 2,900 accessesView PDFCite
Research ArticleOpen accessIn the abstractCrop Yield Prediction in Niger Using Machine Learning TechniquesMahaman Lawali Inoussa Garba, Naroua Harouna, Chaibou Kadri et al.Agriculture is the most impactful sector on Niger's economic growth. Stresses related to climate change and the environment are leading to a continuous decline in crop yield. Accurate crop yield forecasting is of paramount importance for farmers, government, policy makers, and other stakeholders to make most appropriate decisions regarding resource allocation and food security. This study examines the power of … …Journal of Computer Science, Vol. 21, Issue 8 · 16 Sep 2025 · 5,792 accessesView PDFCite
Research ArticleOpen accessIn the abstractTree Volume Prediction Model of Cupressus lusitanica Species: in North-Western Highlands of EthiopiaYishak Adgo Kassie, Abebaw Alene YallewA significant basis of raw materials for the forest products industry is provided by Cupressus lusitanica, one of the commercial timber tree species found in the forest. Accurate tree and stand volume development models are necessary for intensive forest management to yield timber. The goal of this study was to develop and validate volume equations for Cupressus lusitanica tree species … …American Journal of Environmental Sciences, Vol. 21, Issue 1 · 26 Aug 2025 · 5,936 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmpirical Study on Modified Pre-Trained CNN Architectures for Fitzpatrick17k Skin Diseases Prediction ModellingSteven Matthew, Nur Afny Catur Andryani, Rojali et al.Preventing missed diagnosis of skin diseases is critical for enhancing patient outcomes. Technology support empowered by AI based algorithms have been recently developed to minimize the burden. Convolutional Neural Networks (CNNs) are increasingly utilized for image classification tasks including skin's diseases prediction modelling. Its advancement architectures such as pre-trained models, VGG16 andResNet50 provide a strong foundation to up-skill the prediction … …Journal of Computer Science, Vol. 21, Issue 7 · 8 Jul 2025 · 3,934 accessesView PDFCite
Research ArticleOpen accessIn the abstractXAI_MLPCNN: A Novel Explainable AI-Based Deep Learning Framework for Stress IdentificationFateh Bahadur Kunwar, Rakesh Kumar Yadav, Hitendra Singh, Nitin TripathiOver the past ten years, there has been a lot of emphasis focusedon the development of Artificial Intelligence (AI) and Machine Learning(ML)-based mental health treatments. To increase practitioners' and patients'trust in AI applications, AI systems need to explain their actions. This iscalled Explainable AI (XAI). While significant progress has been achievedin stress prediction models, XAI has not advanced as much. … …Journal of Computer Science, Vol. 21, Issue 5 · 6 May 2025 · 6,161 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel River Meander Migration and Cutoff Model: A New PerspectiveYoussef Ismail HafezAccurate prediction of river meander migration is crucial for effective river management and operation, particularly in light of climate changes and human-induced interventions. Existing models often rely on single-equation approaches, such as bank erosion rate versus excess bank velocity or excess bank shear stress, which limit their ability to comprehensively capture the complex dynamics of meander evolution. This study presents … …American Journal of Environmental Sciences, Vol. 21, Issue 1 · 21 Mar 2025 · 7,683 accessesView PDFCite