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224 articles for “neural network prediction”
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Numerical simulation and Artificial neural network illustration of phase-change material integrated into lattice structures printed in 3D
Abstract: This work examines the phase change material (P.C.M.) deposited in various lattice formations—such as “S.C., B.C.C., and F.C.C”.—at varied characteristics. The test concentrates on comprehending heat transport properties and thermal activity throughout the “melting and solidification processes”. The heater's maximum temperature, P.C.M. “melting and solidification”, and Nusselt number are among the essential factors examined. According to the findings, the heater's maximum temperature drops as porosity increases. Although the Nusselt values …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 175–183 Read article
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PREDICTING THE COMPRESSIVE STRENGTH OF CONCRETE USING ANN IN MATLAB
Abstract: This research work focuses on the production of Artificial Neural Networks ( ANNs) in the prediction of concrete compressive strength after 28 days. The measurement of the compressive strength of concrete in situ by means of cores cut from hardened concrete is recognised as the most common technique, but the compressive strength of concrete is very difficult to predict because several factors affect it.In this paper , in order to …
Published in Journal of Construction Engineering, Technology & Management · Vol. 10, Issue 3, 2020 · pp. 46–52 Read article
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AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 Read article
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Applications of Artificial Neural Network in Construction Engineering and Management: An Academic Literature Review and Direction for Future Research
Abstract: One of the artificial intelligence topics is artificial neural network in whichdata processing system is the idea of the human brain.The cause of processing data is many processorsthat treat in parallel form in order to solve the problem.The applications of artificial neural network with neuron model and different network architecture can be used to estimate, predict and modelling of complex problems in construction management. In order to bridge the gap …
Published in Journal of Construction Engineering, Technology & Management · Vol. 6, Issue 1, 2016 · pp. 24–38 Read article
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Detection of Pneumonia in COVID-19 Patients Using X-ray Images
Abstract: This study explores the use of chest X-ray image analysis and deep learning methods to identify pneumonia in COVID-19 patients. Due to the pandemic, Proper as well as immediate examination of COVID-19 is now essential for patient care and disease control. This study proposes a novel approach that uses convolutional neural networks (CNNs) to automatically predict pneumonia in COVID-19 patients using chest X-ray images. In this study, an X-ray of …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 13–23 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Application of Artificial intelligence in Single Point Incremental Forming for Surface Roughness Prediction
Abstract: The sheet metal forming industries always try to find an emerging trend to form sheet-metal in a cost-effective manner. In this regard, a forming technique is trending termed as single point incremental forming (SPIF) in which a simple forming tool having hemispherical end rod is moving and simultaneously deforming the clamped metal sheet according to predetermined toolpath command and forms a complete shape. The achievement of required surface quality is …
Published in Journal of Polymer & Composites · Vol. 12, Issue 1, 2024 · pp. 237–246 Read article
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A Machine Learning-Based Non-Invasive System for Blood Group Prediction Using Fingerprint Biometrics
Abstract: The research is targeted at the creation of innovative solution "Fingerprint Based Blood Group Prediction" for instant, non-invasive blood group determination from analysis of finger impressions, a breakthrough possibility in emergency health care. Sophisticated machine learning can be employed to map fingerprint patterns to corresponding blood group information and overcome the current lack of a direct connection between the two. Integration of various technologies: employed React for frontend development, Flask …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 9–18 Read article
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Literature Review and Discussion of Machine Learning Algorithms for Predicting Chronic Kidney Disease
Abstract: Being one of the most serious and most occurring diseases in our era, chronic kidney disease requires a fast and correct diagnosis. The usage of machine learning in medicine has now grown to such a level that it could be a means of diagnosis. The doctor can be the first one to get the ailment by using machine learning classifier algorithms. This has been the data science sector’s new horizons, …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 34–39 Read article
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ANN Approach to Forecasting the Strength of Nano Silica Incorporated Geopolymer Composite
Abstract: Coal and steel industry by-products, such as fly ash (FA) and blast furnace slag (GGBS), have gained significant attention as precursors for geopolymer concrete (GPC) due to their high aluminosilicate content, offering a sustainable alternative to conventional cement. Nano silica (NS), recognized for its exceptional pozzolanic activity and ability to refine microstructure, has shown potential to enhance the mechanical and durability properties of GPC. This study investigates the influence of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 267–278 Read article
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Artificial Intelligence in Entomology: Global Advances, Applications, and Future Directions in Insect Research and Pest Management
Abstract: Artificial Intelligence (AI) is transforming entomology by enabling scalable, data-driven approaches to insect identification, ecological monitoring, and sustainable pest management. This review synthesizes recent global advances in AI applications across taxonomy, behavioral ecology, predictive modeling, and precision agriculture. Machine learning and deep learning techniques—including convolutional neural networks, acoustic classification models, and ensemble predictive algorithms—have demonstrated high classification accuracies (often exceeding 90% under controlled conditions) and improved early detection of pest …
Published in International Journal of Insects · Vol. 3, Issue 1, 2026 · pp. 29–40 Read article
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Intelligent Power Quality Enhancement Strategies for PV-Integrated Smart Distribution Networks: A State-of-the-Art Review
Abstract: The rapid integration of photovoltaic (PV) systems into modern power distribution networks has introduced significant challenges related to power quality. Issues such as voltage fluctuations, harmonic distortion, flicker, and reactive power imbalance arise due to the intermittent and nonlinear nature of solar energy generation. This paper presents a concise literature review of various power quality enhancement techniques employed in PV-integrated networks. Key approaches include the use of active power filters …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 30–53 Read article
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Use of Intelligent Control Systems to Manage Traffic Effectively and Productively
Abstract: Intelligent control system is the advanced technology in which the collected data is provided to A.I. and with the help ofvarious methods like machine learning, neural networks, Bayesian probability, fuzzy logic the solution to a particularproblem is found.In a country’s growth the traffic management plays a great role as the maximum industries depends on the highways orroads and when it is well planned it can reduce the commute time and …
Published in Trends in Mechanical Engineering & Technology · Vol. 13, Issue 1, 2023 · pp. 22–27 Read article
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Prediction of Mechanical Properties for Advanced Engineering Applications utilizing Polymer Composite Materials by Machine Learning
Abstract: Polymer composites show great promise as engineering materials because of their mechanical performance, resistance to corrosion, lightweight nature, and adaptability in design. Aerospace, automotive, biomedical, maritime, and civil engineers all rely on mechanical property prediction to cut down on trial expenses, expedite product development, and optimize material selection. Speedy design optimization is not possible using traditional numerical and experimental methods due to the high costs associated with material characterisation, computational …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1258–1284 Read article
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A Study of Cloud-Enabled Deep Learning for Monitoring and Predicting Soil Health in Agriculture
Abstract: Soil health is a critical factor in ensuring sustainable agricultural practices and food security. Traditional methods for soil health assessment are often time-consuming, localized, and lack scalability. This study explores the integration of cloud-enabled deep learning techniques to monitor and predict soil health efficiently. Leveraging data from IoT sensors, satellite imagery, and lab-based analyses, a cloud-based framework is proposed to process and analyze soil health parameters such as pH, moisture …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 8–16 Read article
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Evaluation and Scientific Investigation: Stock Market Forecasting Techniques
Abstract: Analysts and scholars have consistently shown interest in predicting stock market trends, a complex task given the multitude of variables influencing stock values. This article includes a thorough analysis of 50 research papers that propose methodology for stock market prediction, including Bayesian models, fuzzy classifiers, artificial neural networks (ANNs), support vector machines (SVMs) classifiers, neural networks (NNs), and machine learning techniques. The collected papers are categorized using various prediction, clustering …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 26–40 Read article
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Tank Water Quality Analysis Using Machine Learning
Abstract: Tank Water quality is a critical factor for public health, agriculture, as well as industry. Continuous monitoring of tank water quality: temperature, humidity, water level, CO2 concentration, and pH, is vital for safe usage. Using machine learning, real-time data analysis can detect anomalies, predict issues, and optimize water management, ensuring timely responses and improved safety. This intelligent approach enhances decision-making and maintains water quality effectively in various environments.We develop an …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 27–34 Read article
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Network Traffic Analysis Using Machine Learning
Abstract: Network traffic analysis and prediction has applications in a variety of fields and has recently attracted a considerable number of studies. To find numerous issues with current computer network applications, various sorts of studies are carried out and reported. A proactive strategy to guarantee safe, dependable, and high-quality network communications is network traffic analysis and prediction. For network traffic analysis, several methods, including data mining and neural network-based methods, are …
Published in Current Trends in Signal Processing · Vol. 12, Issue 3, 2022 · pp. 17–23 Read article
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Support Vector Machine Inspired Load Forecasting of a State University in Haryana
Abstract: Estimating the possible environmental impact and determining probable capital requirements are made easier with a solid grasp of electricity demand. Beginning in the middle of the 20th century, demand forecasting for electric power networks was studied theoretically. Prior to that, the study of demand forecasting had not developed because of the small scale of power networks. With the use of statistical prediction techniques, plans for the electric power industry have …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 33–40 Read article
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Process of Decolourisation of Textile Dye Using Electrocoagulation and It’s Modelling Using Artificial Neural Network
Abstract: Electrochemical technology encompasses a wide spectrum of technologies and makes numerous contributions towards a cleaner environment. In this work, the decolourization of the synthetic fabric dye solution containing CIBA (Company for Chemical Industry Basel) Red by electrocoagulation method has been investigated. Investigations have also been conducted on the impact of operational variables on colour removal effectiveness, including beginning pH, electrolysis duration, distance between electrodes. An electrode retention time, dye focus. …
Published in Trends in Electrical Engineering · Vol. 14, Issue 2, 2024 · pp. 28–38 Read article