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1074 articles for “prediction system”
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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Thermal Performance Analysis of Flat Plate Solar Collector and Solar Dryer of Indirect Solar Drying System
Abstract: The objective of this study is to investigate the thermal performance of a flat plate solar collector and solar dryer experimentally. The expressions for efficiency of solar collector andsolar dryer with phase change material (PCM) storage system in quasi-steady state conditions have been derived. The analysis is based on the basic energy balance forthe system. A computer model has been developed to predict the various performance parameters of the solar …
Published in Journal of Thermal Engineering and Applications · Vol. 2, Issue 3, 2015 · pp. 21–31 Read article
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Performance Analysis of Mobility over the Integrated UMTS and WLAN Network in different Mobility Models with Vertical Handoff Prediction Algorithms using Streaming Service
Abstract: The seamless mobility is the final goal of any heterogeneous network. It can be achieved by selecting a suitable vertical handoff prediction algorithm, which can perform well in different mobility models. This paper presents comparative performance of mobility over the integrated universal mobile telecommunications system (UMTS) and wireless local area network (WLAN) in different mobility models (the file-based mobility model and the random waypoint mobility model) with vertical handoff prediction …
Published in Recent Trends in Electronics Communication Systems · Vol. 3, Issue 1, 2016 · pp. 35–47 Read article
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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 45–54 Read article
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Wildfire Detection and Tracking System
Abstract: To create a precise forecast of the wildfire, it is crucial to possess the capability to recognize it and anticipate how it will distribute. The devastation of vegetation, the loss of assets, the rise in greenhouse gases, the extinction of Numerous animal species and even human fatalities can all result from wildfires. To trim back this danger, there must be a mechanism capable of detecting a fire the moment it …
Published in International Journal on Drones · Vol. 2, Issue 2, 2026 · pp. 21–29 Read article
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CNN-based Approach for Efficient Bell Pepper Leaf Disease Recognition
Abstract: Convolutional Neural Networks (CNNs) have achieved remarkable results in the detection of diseased plant leaves, providing highly accurate predictions. This project offers a comprehensive examination of existing systems designed for the detection of plant-based diseases. Using CNN trained on a dataset of bell pepper plant images, various simulation approaches for neurons and layers were employed. Plant diseases have significant impacts on agricultural productivity, leading to economic losses, reduced crop quality, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 10, Issue 3, 2023 · pp. 16–22 Read article
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DATABASE-DRIVEN ENERGY MANAGEMENT IN ELECTRIC VEHICLES
Abstract: With the growing concern over environmental pollution, there is an increasing demand for sustainable and eco-friendly technologies. Among these, electric vehicles (EVs) have emerged as a promising alternative to conventional fossil-fuel-based transportation. However, as EV adoption accelerates, efficient energy management becomes critical to enhance vehicle performance, extend battery life, and ensure overall system reliability. This research presents a Database-Driven Energy Management System (DBEMS) that leverages real-time data from EV components …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 19–24 Read article
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Toxicology 4.0: Integrating Artificial Intelligence, Big Data, Health Informatics, and Precision Analytics for Predictive Toxicity Assessment, Real-Time Toxicovigilance, and Personalized Patient Safety
Abstract: Background: Toxicology is undergoing a major transformation, increasingly described as Toxicology 4.0, driven by the integration of artificial intelligence (AI), big data analytics, health informatics, and precision analytics. Conventional toxicity testing is limited by high costs, lengthy timelines, and challenges in translating animal and low-throughput in vitro findings to humans. Aim and Objectives: To comprehensively evaluate the emerging role of Toxicology 4.0 in predictive toxicity assessment, real-time toxicovigilance, and personalized …
Published in Research and Reviews: A Journal of Toxicology · Vol. 16, Issue 2, 2026 Read article
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Design of a Technique to Improve Software Maintenance Using Fuzzy Logic
Abstract: AbstractMaintainability is one of the most important aspects of software development. In that, maintenance costs account for at least 60–65% of total software lifetime costs. Software quality is the most important factor in the development of any software, which can depend on many quality attributes. Fuzzy logic is one of the techniques, which can be used to establish the relationship between object oriented metrics and software maintainability. In this paper …
Published in Journal of Web Engineering & Technology · Vol. 3, Issue 3, 2016 · pp. 21–27 Read article
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A Review on Predicting Wear and Friction of PTFE Composites - Fillers to Machine Learning Models
Abstract: Polytetrafluoroethylene (PTFE) composites, a self-lubricating material with low friction, became an indispensable material in engineering applications where load carrying capacity and wear are crucial. The pure PTFE has poor mechanical strength and wear resistance which can be enhanced by the addition of fillers in appropriate volume fraction. The wear performance is dependent on various factors such as fillers, operating parameters, environmental conditions as well as manufacturing attributes. This makes the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 114–128 Read article
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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AI in Pharmacy Automation: A Review of Innovations in Robotics, Their Ethical Implications, and Impact on Workflow and Workforce
Abstract: The pharmacy profession has witnessed a paradigm shift with the integration of robotics and artificial intelligence (AI) in automation. Traditional practices that relied heavily on manual dispensing, paper documentation, and technician labor are now being augmented or replaced by robotic dispensing systems, sterile compounding machines, and predictive AI algorithms. These innovations enhance safety, improve efficiency, and reduce errors, while also raising complex ethical questions related to workforce displacement, liability, and …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 17, Issue 1, 2026 · pp. 01–07 Read article
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Controlling of Level Process in Non-Linear System Using Variable Frequency Drive
Abstract: Abstract—The objective of this paper is to investigate the Model Predictive Control (MPC) strategy, analyze and compare the control effects with Proportional-Integral-Derivative (PID) control strategy in maintaining a level of spherical tank system using VFD. An advanced control method, MPC has been widely used and well received in a wide variety of applications in process control, it utilizes an explicit process model to predict the future response of a process …
Published in Current Trends in Information Technology · Vol. 9, Issue 2, 2019 · pp. 24–33 Read article
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Advanced Digital Twin and AI Integration for Real-Time Optimization in Polymer Production
Abstract: The integration of Internet of Things (IoT) with Artificial Intelligence (AI) technologies opens up considerable avenues for reshaping polymer manufacturing by improving operational effectiveness, securing exceptional product standards, and advancing sustainability in the environment. This academic manuscript delineates an advanced framework that integrates IoT and AI with synergistic technologies, including blockchain, edge computing, and digital twin methodologies, to revolutionize polymer manufacturing processes. The proposed architecture utilizes IoT sensors for the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 81–89 Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 Read article
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Material-Integrated Energy Management: Role of Advanced Polymers and Composites in Smart Homes
Abstract: The article discusses the possibility of improving the performance as well as the sustainability of smart-home-based energy management systems (EMS) by applying advanced polymeric and composite materials. Smart homes today are placing greater requirements on lightweight, thermally stable, high durability, and electrically conducting compounds in such important aspects of the devices as batteries, substrate layers in solar panels, thermally resistant enclosures, and high efficiency thermal insulation on intelligent appliances. Such …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1361–1374 Read article
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Atmospheric Boundary Layer Processes: Impacts on Weather Patterns and Climate Change
Abstract: The atmospheric boundary layer (ABL) is a vital component of the Earth's climate system, acting as the interface between the terrestrial surface and the overlying atmosphere. This layer, typically extending from the surface to a height of a few hundred meters, is characterized by strong gradients in meteorological variables such as temperature, humidity, wind speed, and atmospheric pressure. Understanding the dynamics of the ABL is essential for comprehending weather phenomena, …
Published in International Journal of Atmosphere · Vol. 1, Issue 2, 2024 · pp. 22–25 Read article
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A Study on Smart Healthcare Innovations
Abstract: The desire for effective, patient-centred solutions and the rapid growth of technology are driving forces in the healthcare industry. The term "smart healthcare innovation" refers to a broad category of approaches, tools, and procedures that are intended to improve patient outcomes, optimize resource use, and enhance overall healthcare delivery. These innovations integrate cutting-edge technologies such as artificial intelligence (AI), the Internet of Things (IoT), wearable devices, big data analytics, and …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 · pp. 63–68 Read article
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The Role of Simulation and Digital Twins in Enhancing Mechanical Production Efficiency: A Systematic Review
Abstract: In the evolving landscape of smart manufacturing, simulation technologies and digital twin (DT) systems have emerged as pivotal tools for enhancing the efficiency, agility, and sustainability of mechanical production processes. This systematic review investigates how the integration of simulations and DTs contributes to performance improvements across various stages of mechanical manufacturing—ranging from design and process optimization to predictive maintenance and real-time monitoring. While simulations provide the ability to model, test, …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 31–36 Read article