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79 articles for “Predictive Models”
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Research ArticleOpen accessAll words, across the recordIoT-Based Smart Hydroponic System for Nutrient Management Using Predictive Machine Learning AlgorithmsPalash Gourshettiwar, K. T. V. ReddyHydroponics, an efficient cultivation method, benefits significantly from the precision and adaptability that Machine Learning (ML) algorithms can offer, along with the real-time monitoring facilitated by the devices using the Internet of Things (IoT). This study summarises the latest research and discusses how Machine Learning and the IoT work together, focusing on nutrient optimization, plant development, and resource efficiency. The … …Journal of Computer Science, Vol. 22, Issue 3 · 11 Mar 2026 · 3,056 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA 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 · 1,882 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordPerformance Prediction Model for Predictive Maintenance Based on K-Nearest Neighbor Method for Air Navigation Equipment FacilitiesRachmat Hidayat, Ditdit Nugeraha UtamaThe aging of air navigation facilities leads to a decline in equipment performance and reliability, posing significant challenges for aviation organizations in the large-scale replacement of outdated systems, as well as in managing budgets and resources. To address these issues, a performance prediction model for equipment was developed using the K-Nearest Neighbor (KNN) method, aimed at enhancing maintenance planning and … …Journal of Computer Science, Vol. 21, Issue 4 · 4 Mar 2025 · 5,661 accessesView PDFCite
Review ArticleOpen accessAll words, across the recordHybrid Machine Learning Framework with Data Analytics Model for Privacy-Preserved Intelligent Predictive Maintenance in Healthcare IoTArun Ganji, D. Usha, P.S. RajakumarFederated Learning (FL) is a cutting-edge approach for developing machine learning (ML) models using distributed datasets while preserving data privacy and ownership. FL is particularly suited for Internet of Things (IoT) networks due to its decentralized nature, which supports In-Edge AI and maintains data locality. However, FL's complexity poses challenges in analyzing system health, making it crucial to develop robust … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,830 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordIntelligent Identification and Sorting of Chinese Herbs Recommend a String-Level Predictive Electromechanical SystemWenyi Zhang, Gang Wang, Xiaofei Xu et al.Based on the analysis of a large number of Chinese medicinal materials, a mobile robot visual function research and development experimental domestic chips electromechanical arm-controller, which was constructed using a typical kernel algorithm recommended by Chinese medicinal materials visual recognition, which the cascade Electromechanical Control System was based on iterative learning electromechanical control for multi-joint manipulators. The original and improved … …American Journal of Biochemistry and Biotechnology, Vol. 20, Issue 2 · 11 Jul 2024 · 4,277 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordComparison of Multiple Linear Regression and Neural Network Models in Bank Performance Prediction in BotswanaHassan Kablay, Victor GumboBank performance is critical to the banking sector and the economy as a whole. In this study, Multiple Linear Regression (MLR) technique and feed forward Neural Network (NN) are used to predict the performance of 11 banks in Botswana. Return on Assets (RoA) is used as the dependent variable, while management quality, credit risk, liquidity, financial leverage and capital adequacy … …Journal of Mathematics and Statistics, Vol. 17, Issue 1 · 10 Jan 2022 · 6,469 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordEvaluating Patient Readmission Risk: A Predictive Analytics ApproachAvishek Choudhury, Dr. Christopher M. GreeneWith the emergence of the Hospital Readmission Reduction Program of the Center for Medicare and Medicaid Services on October 1, 2012, forecasting unplanned patient readmission risk became crucial to the healthcare domain. There are tangible works in the literature emphasizing on developing readmission risk prediction models; However, the models are not accurate enough to be deployed in an actual clinical … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 4 · 7 Dec 2018 · 8,161 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordThai Expressive Speech Processing Technology: A ReviewSuphattharachai ChomphanProblem statement: The studies on Thai expressive speech or emotional speech have been conducted for years. Most of them are expected to analysis the characteristics of Thai expressive speech. However, the conclusive reviews on these studies have not been conducted for further study on the speech technology or application of Thai expressive speech. Approach: The review of research on Thai … …American Journal of Applied Sciences, Vol. 9, Issue 3 · 12 Jan 2012 · 6,736 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA HYBRID INTELLIGENT MODEL FOR SOFTWARE COST ESTIMATIONWei Lin Du, Luiz Fernando Capretz, Ali Bou Nassif, Danny HoAccurate software development effort estimation is critical to the success of software projects. Although many techniques and algorithmic models have been developed and implemented by practitioners, accurate software development effort prediction is still a challenging endeavor in the field of software engineering, especially in handling uncertain and imprecise inputs and collinear characteristics. In this study, a hybrid intelligent model combining … …Journal of Computer Science, Vol. 9, Issue 11 · 28 Sep 2013 · 7,748 accessesView PDFCite