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1074 articles for “prediction system”
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Hybrid Feature Selection Approach for Stability Prediction for Intracerebral Hemorrhage Patients
Abstract: Intra Cerebral Hemorrhage (ICH) stability estimation is useful for enhancing diagnosis accuracy, selecting the best course of treatment, and clinically evaluating variations with healthy individuals. Due to their low predictive value, the clinical application of several ICH progression scoring systems is constrained. The dataset includes clinical parameters including age, Glasgow Coma Scale (GCS), and CT Angiography (CTA) spot that have been retrieved using geometric features from the segmented bleeding volume …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 2, 2022 · pp. 9–17 Read article
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Detailed review on adsorption refrigeration system for different adsorbent/adsorbate working pair green composite materials – An environmental aspect
Abstract: Adsorption refrigeration is one of the greatest encouraging system for the refrigeration applications due to use of low grade energy. Present study deals with detailed review of adsorption refrigeration system. This article mainly concern with adsorption refrigeration arrangement by the utilization of most appropriate operational pairs namely activated carbon/methanol, silica gel/water and zeolite/water. Detail review carried out to predict thermal analysis and performance of the system. Mechanical properties of the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 1–9 Read article
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Prediction of Punching Shear Capacity of Biaxial Voided Slab
Abstract: Biaxial voided slab systems are advantageous due to their reduced self-weight, up to 50 % in comparison with the conventional reinforced concrete solid slab. The reduction in the concrete cross sectional area reduces the shear capacity up to about 40 %. The prediction of punching shear capacity in voided slab is not direct unlike in solid slab. This is because the presence of voids alters the critical failure section and …
Published in Journal of Structural Engineering and Management · Vol. 6, Issue 2, 2019 · pp. 24–33 Read article
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A Linear Regression Model Used to Analysis the Tesla Stock Price Prediction Using Machine Learning
Abstract: The stock market is a fascinating sector of the economic research. It comes in a number of varieties. Several specialists have been examining and investigating the several patterns that the stock market experiences fluctuations. Predicting the stock values of different companies using historical data has been one of the primary research projects. Stock price prediction can help people a great deal by helping them understand where and how to invest, …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 2, 2024 · pp. 8–13 Read article
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Energy-efficient HVAC System with Decision Tree Classifier and Real-time SMS Notification
Abstract: This research paper explores the design and implementation of an energy-efficient heating, ventilation, and air conditioning (HVAC) system aimed at optimizing energy consumption and enhancing operational efficiency. The system incorporates high-efficiency components, including axial flow fans, motors, and intelligent variable frequency drives, achieving an overall system efficiency of up to 85%. By utilizing both static and dynamic pressures, the HVAC system operates more effectively under varying conditions compared to traditional …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 2, Issue 2, 2024 · pp. 29–34 Read article
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“Automated Real-Time Transformer Health Monitoring System Using IoT”
Abstract: Transformers play a crucial role in the architecture of electricity production and distribution. To guarantee that a transformer performs successfully and efficiently, performance must be closely monitored. Manual and time-consuming procedures are used to monitor transformer characteristics such oil level, temperature, and pressure. To solve this issue, an IoT-based transformer parameter monitoring system may be a good choice. Designing and implementing an IoT-based transformer parameter monitoring system that enables real-time …
Published in Journal of Semiconductor Devices and Circuits · Vol. 10, Issue 1, 2024 · pp. 16–23 Read article
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Enhancing Construction Safety Performance Through Artificial Intelligence: A Systematic Review
Abstract: The construction industry is still one of the most dangerous sectors globally because of its dynamic working environment, the employment of heavy machinery, and the complexity of operational processes. Traditional safety management methods are largely dependent on manual monitoring and reactive measures, which are not always effective for accident prevention. In recent years, Artificial Intelligence (AI) has been recognized as a revolutionary technology in construction safety, with capabilities such as …
Published in Journal of Industrial Safety Engineering · Vol. 13, Issue 1, 2026 · pp. 13–30 Read article
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Analysis of Disease and Risk Prediction using ML
Abstract: This paper comprises of efficient machine learning algorithms used in predicting diseases through symptoms. As, the health industry has a huge amount of data for various fields, so we want to make a system where we can use various other applications of machine learning on health industry. This all had been done to make better medical decisions and also for rise in the accuracy. As an accurate analysis and early …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 7, Issue 1, 2020 · pp. 7–13 Read article
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Generalized Churn Prediction
Abstract: Abstract: Customer churn evaluation and management are important to determine the loyalty of customers with the firm and thus to remain aware of each customer whether he will stay or leave the firm. This, in turn, will be used to determine the value of the firm and hence its place in the market. This paper includes existing literature which has been done in the field of churn analysis from time …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 3, 2019 · pp. 19–24 Read article
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Computational Screening of Vitex negundo Compounds for Potential Arthritis Therapies in India
Abstract: Objective: Arthritis is a pervasive medical condition that manifests as inflammation and discomfort within the joints. As of September 2021, arthritis has affected an estimated 180 million people in India, making it a substantial public health concern with a considerable impact on individuals' quality of life and healthcare systems. Therefore, using molecular docking, drug-likeness prediction, and ADME analysis, an effort was made to identify natural compounds from Vitex negundo, which …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 1, 2024 · pp. 01–18 Read article
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Pre-extension Demonstration of Improved Teff Technologies at Shashogo District, Hadiya Zone, Southern Ethiopia
Abstract: Teff is a highly important crop in Ethiopia in terms of both production and consumption. Population growth, low incomes, and urbanization have all contributed to an increase in demand for teff, which is predicted to continue. However, the teff production system largely depends on traditional methods. As a result, the crop yield has not reached at the desired level. Therefore, the pre-extension demonstration of improved teff technologies was conducted at …
Published in Research & Reviews : Journal of Ecology · Vol. 12, Issue 1, 2023 · pp. 33–39 Read article
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Artificial Intelligence–Driven Decision Support Systems for Smart and Efficient Data Analysis
Abstract: Artificial Intelligence (AI) has emerged as a transformative technology reshaping the way organizations process information, analyze data, and support decision-making. With the rapid growth of digital data across sectors, traditional analytical methods often face limitations in handling large, complex, and dynamic datasets. AI-based techniques, particularly machine learning and intelligent decision support systems, provide advanced capabilities for identifying hidden patterns, predicting outcomes, and assisting in data-driven decisions. This paper examines the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Physics-Adaptive Digital Twin with Neural-Operator Reduced-Order Modelling
Abstract: This study proposes a novel Physics-Adaptive Digital Twin with Neural-Operator Reduced-Order Modelling (PADT-NO) framework for predictive modelling of complex, nonlinear, and multiscale fluid flows. The proposed mathematical framework integrates fundamental conservation laws, Navier–Stokes dynamics, physics-constrained neural operators, adaptive reduced-order modelling, and uncertainty-aware state estimation within a unified computational architecture. Unlike conventional computational fluid dynamics and purely data-driven approaches, the proposed model dynamically couples high-fidelity physical information with a low-dimensional latent …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 2, 2026 · pp. 89–103 Read article
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The Role of Artificial Intelligence in Mental Health: Applications in Neurodegenerative Disorders
Abstract: Artificial intelligence (AI) has significantly changed many aspects of medical care, particularly the early evaluation, therapy, and management of neurodegenerative illnesses like Alzheimer's, disease, Parkinson's diseases, and Huntington's diseases. The current research explores the application of AI in mental health with respect to neurological disorders, especially advancements in cognitive examination, neuroimaging analysis, predictive modeling, and customized therapy modalities. Artificial intelligence (AI) systems have shown enormous potential in detecting minute biomarkers …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 3, 2025 · pp. 34–40 Read article
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Future-Ready Communication Systems: Exploring High-Speed, Adaptive, and Secure Network Solutions
Abstract: The domain of electronics communication systems has experienced rapid transformation due to the growing demand for high-speed, reliable, and intelligent communication networks. This paper presents a comprehensive analysis of emerging trends such as Fifth Generation (5G) communication systems, Internet of Things (IoT), Artificial Intelligence (AI)-enabled networks, Software-Defined Networking (SDN), optical communication advancements, and cybersecurity mechanisms. The combination of cloud computing, edge computing, and network virtualization which improve system flexibility, allow …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 1, 2026 · pp. 32–38 Read article
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Exploring Antimalarial Activity of Chalcone Derivatives through QSAR
Abstract: Background: The core structure of chalcones contains a reactive α,β-unsaturated system within the aromatic rings, which plays a key role in mediating various biological effects. These effects include enzyme inhibition, anticancer activity, anti-inflammatory properties, as well as antibacterial, antifungal, antimalarial, antiprotozoal, and anti-filarial actions.Modifying the structure by introducing substituent groups to the aromatic ring can enhance potency, reduce toxicity, and expand their range of pharmacological actions.Methods: A total of twenty-seven …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 1–6 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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Fault Detection in Solar PV Systems Integrated with the Power Grid: Evaluating Logistic Regression through Confusion Matrix Analysis
Abstract: This paper proposes a method for failure detection in grid-integrated solar photovoltaic (PV) systems using logistic regression and real-time sensor data. The approach effectively classifies and identifies seven distinct fault types. The developed model demonstrates a high fault identification accuracy, ranging from 93% to 96.5% across various fault types and operational conditions. By leveraging logistic regression, the system utilizes key independent variables that significantly influence the classification process. Additionally, the …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 2, 2025 · pp. 45–52 Read article
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Forecasting Climate-Driven Healthcare Demand in Agricultural Regions: A Multi-Modal AI Approach
Abstract: The rapidly increasing instability of world climatic regimes has made past meteorological thresholds irrelevant, especially in the agricultural areas where monetary stability and well-being of humans are closely intertwined with an environmental situation. The more the frequency of 1 in every 1000-year events, i.e., heatwaves and catastrophic flooding increase, the greater the rural healthcare systems are in crisis, i.e., unable to predict a surge in demand because of data scarcity, …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 28–38 Read article
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Differential Model of Wave Vibration on Strings and Rods
Abstract: Vibration, as a physical phenomenon, plays a multifaceted role in both natural and engineered systems. Beyond its essential contribution to communication through sound and speech, it finds critical application in various technological domains. For instance, in the design of stringed musical instruments such as violins and guitars, precise manipulation of string vibrations defines tonal quality and musical resonance. Similarly, metal rods in tuning forks exhibit vibrational properties that are finely …
Published in Research & Reviews : Journal of Physics · Vol. 14, Issue 1, 2025 · pp. 17–21 Read article