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193 articles for “forecasting model”
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Advancing Healthcare Systems: A Machine Learning Approach to Multi-Disease Prediction
Abstract: The integration of machine learning algorithms in healthcare has revolutionized the way we approach disease prediction and diagnosis. An attempt to employ machine learning techniques to forecast numerous diseases is presented in this study. A diverse dataset containing patient records, medical history, and relevant features for various diseases was used to develop predictive models. Feature selection and normalization were among the preprocessing methods used to clean and prepare the data. …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 1, 2025 · pp. 1–6 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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Smart Education through Machine Learning: A Review of Trends, Benefits, and Risks
Abstract: Machine learning (ML) is transforming the contemporary education by transforming it into smarter, data-driven and personalised learning. This review examines the key tendencies, advantages, and possible threats of applying ML in intelligent education. ML promotes adaptive learning, automatization of assessments, and student engagement, which is highly beneficial both to learners and educators. Nonetheless, issues like data privacy, algorithmic bias or unequal access are also a significant concern. The article emphasises …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 · pp. 24–28 Read article
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Comparison of Hard Wood Functional Parameters on the Deliverability using Buckingham Pi Theorem: The Concept of Procurement
Abstract: This investigation was able to address the effect of wood density and weight on the tensile strength and deliverability of the truck performance and as medium to forecast the procurement plan for cost optimization. This was achieved using the Buckingham Pi Theorem by considering the necessary constrain factors as presented in the development of the model. Indeed, the study demonstrates the significance of wood density and wood weight on truck …
Published in Journal of Petroleum Engineering & Technology · Vol. 12, Issue 3, 2022 · pp. 19–27 Read article
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Study of Structures Considering Second Degree Analysis P-delta and Construction Sequence Analysis
Abstract: Infrastructure plays an important, rathernecessary role in modern society.Real estate amenities surrounding to us give everyone access to multiple aspects of technology which help to carve the frame of mind.Amenities, which once were rare and difficult to avail for everyone, is now available to common civilians.Recently, RCC structures has changed a lot,the symmetrical and identical storeys of premises is now considered as a conventional and to an extent inefficient design.The …
Published in Journal of Structural Engineering and Management · Vol. 8, Issue 1, 2021 · pp. 38–42 Read article
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Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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Personalized Nutrition and Exercise: Pioneering the Path to Precision Medicine
Abstract: Preventive healthcare is about to undergo a major shift thanks to the personalised exercise and nutrition paradigm, which is based on precision medicine concepts. In order to create tailored recommendations for improving health outcomes and preventing chronic diseases, this article explores the integration of genetic profiling, metabolic evaluation, and lifestyle factors. A person's response to food and exercise depends heavily on genetic and metabolic variances, which emphasises the need of …
Published in Emerging Trends in Personalized Medicines · Vol. 1, Issue 2, 2024 · pp. 42–46 Read article
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Strategies for Efficient Integration of Distributed Energy Resources into Microgrid Systems
Abstract: With the growing integration of Distributed Energy Resources into modern power systems, the global energy landscape is changing. Some of the DERs are solar photovoltaic (PV), wind turbines, battery storage systems, combined heat and power (CHP) units, and electric vehicles (EVs). Some of the advantages include lower transmission losses, better energy efficiency, and more resilience to grid failures. However, the far-reaching integration of DERs carries with it considerable technical, economic, …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 51–56 Read article
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AI-Driven Innovation in Biomaterials: Predictive Modeling and Design for the Future
Abstract: The integration of artificial intelligence (AI) is revolutionizing the field of biomaterials, paving the way for innovative approaches in their development and production. This paper examines the connection between AI and biomaterials, emphasizing the substantial impact of predictive modeling on the evolution of the field. By examining recent research and cutting-edge uses, the document shows how AI-powered predictive modeling has revolutionized biomaterial design, marking a period of unparalleled precision and …
Published in Trends in Machine design · Vol. 11, Issue 3, 2024 · pp. 25–35 Read article
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Parametric optimization and validation of novel 3D scanning approach for sustainable manufacturing of patient-specific orthodontic retainers
Abstract: The purpose of the proposed study is to identify the ideal procedure parameters for 3D scanning a denture in order to produce customised orthodontic retainers that can be produced sustainably. However, pilot investigations rarely explore parameters like scanning angle, light intensity, or scanning distance. In order to lower acquisition error, the suggested study examines a method for forecasting the ideal values of the previously indicated scanning parameters. Based on the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 265–278 Read article
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Next-Generation Satellite Remote Sensing: Innovations, Applications, and Future Prospects
Abstract: Advances in satellite remote sensing have revolutionized our ability to monitor, analyze, and understand the Earth's environment across various scales. Over the past few decades, the field has seen remarkable progress in sensor technology, data processing techniques, and analytical methodologies. Modern satellites now provide high-resolution imagery and multi-spectral data, enabling enhanced monitoring of land cover, atmospheric conditions, oceanic dynamics, and natural disasters. These advancements have facilitated improvements in climate change …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 1, 2025 · pp. 37–62 Read article
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Forecasting of Factors Affecting Thermiston Work Productivity Estimation by Using Artificial Neural Network
Abstract: The research aims to find factors affecting of Thermiston work productivity and the derivation of an equation to predict the rates of Thermiston work productivity by using artificial neural network technology and compared with traditional methods. The Artificial Neural Network with multilayer by back-propagation error technique for modeling the productivity estimation is used, it is founded that the ANN are able to manage to, can predict the productivity for Thermiston …
Published in Journal of Construction Engineering, Technology & Management · Vol. 7, Issue 1, 2017 · pp. 10–21 Read article
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Predicting Student Placement Readiness: A Machine Learning Approach Using Coding Activities and Multi-Dimensional Performance Indicators
Abstract: In the modern information-driven academic world, identifying student employability and placement preparedness has predicted. be made a part and parcel of academic planning and career. development. This study provides a machine learning-based. structure to evaluate and forecast student placement pre-paredness by combining various performance aspects-academic achieve- ment, coding activity, aptitude and behavioral engage-ment metrics. Multi-source was gathered and preprocessed in the study. student information, such as student records (CGPA, attendance), …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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Enhance the Thermal Performance and Fluid Flow Behavior in Micro-Tube Heat Exchangers with Variable Fluid Properties for Cooling Applications
Abstract: This paper focus on the substantial effects of fluid property changes and phase change events, this study provides a comprehensive transient assessment of the heat exchanger's thermal performance and fluid flow behaviour for cooling and dehumidification applications. In response to a step-change perturbation, a dynamic model was created and co-simulated to describe the moist air (shell-side) and the two-phase refrigerant (tube-side), as well as their non-linear interactions. The significant correlation …
Published in Journal of Thermal Engineering and Applications · Vol. 13, Issue 2, 2026 Read article
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Multi-phase Flow Simulation Using Computational Fluid Dynamics
Abstract: Computational fluid dynamics (CFD)-based multi-phase flow simulation is a fast developing topic with broad applications in many scientific fields and industry. An extensive account of current developments, difficulties, and uses in multi-phase flow simulations is given in this review paper. Important modeling strategies, numerical methods, validation procedures, and new developments in CFD-based multi-phase flow analysis are covered. This paper is to contribute to the ongoing development and use of CFD …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 1, Issue 2, 2023 · pp. 28–34 Read article
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Hybrid Machine Learning and Finite Element Framework for Predicting Damage Behavior in Fiber-Reinforced Polymer Composites
Abstract: Fiber Reinforced Polymer (FRP) composites have broad spread use in aerospace, automotive, marine and structural applications due to its high specific strength, stiffness and corrosion resistance. The various damage mechanisms such as matrix cracking, fiber breakage, delamination and interfacial failure, however, make the forecasting of damage particularly complex. In this work, a hybrid machine learning (ML) and finite element (FE) system is proposed for predicting the damage behavior of FRP …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Unified Ensemble Techniques for Enhanced DDoS Attack Prevention and Detection
Abstract: Today’s world is entirely reliant on the internet. The internet is a worldwide information source that all users rely on, hence its accessibility is critical. There have been reports in recent years, particularly in the information and technology division of significant organizations worldwide, of data breaches where the terms denial-of-service (DoS) and DDoS are consistently present in the stolen material. Network security is seriously threatened by DoS attacks. They have …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 20–27 Read article
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Smart Water Harvester
Abstract: Smart water harvester is a wiser use of Data Science in the optimization of rainwater harvesting, taking into account the forecast of precipitation and ideal catchment areas, and basically image processing using machine learning. In that respect, the system, via predictive algorithms like Random Forests, predicts the amount of rainfall by taking into consideration historical and real-time data, while Digital Elevation Models (DEM) and visualization methodologies of images make geographical …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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Enhancing Production Line Efficiency: Simulating and Optimizing Single and Parallel Line Processes
Abstract: During a time of fast-paced industrial growth, increasing production line effectiveness is a core issue for manufacturers looking to maximize output, reduce waste, and stay competitive. This study explores the use of simulation-based optimization methods to enhance single and parallel production line designs. Stepping beyond traditional trial-and-error methods, the research utilizes Siemens Tecnomatix Plant Simulation to simulate actual manufacturing scenarios, considering intricacies like buffer capacities, machine sequencing, and event-driven scheduling. …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 22–32 Read article