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224 articles for “neural network prediction”
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Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article
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Digital Transformation of Urban Infrastructure with the Help of AI Guardians
Abstract: The construction industry continues to face challenges related to quality control, safety protocols, and meeting project deadlines. These issues often result in significant cost overruns and project delays. Traditional inspection and site management approaches rely heavily on manual work and individual judgment. As a result, human errors can easily occur, and these methods provide only limited snapshots of site conditions over time. This paper presents a comprehensive framework that uses …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 16–25 Read article
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FACE EMOTION RECOGNITION TO DETECT DEPRESSION
Abstract: In the current competitive world, one of the most familiar and grave mental illness we encounter in humans is Depression also called as major depression or major depressive disorder. It makes you feel depressed and disinterested all the time, which has a bad impact on your thoughts and behaviour. Thus affecting not only the victim but also people associated with them, such as family, friends and society. If not treated …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 1–14 Read article
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A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article
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Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 386–407 Read article
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Artificial Intelligence in Medical Fields
Abstract: Artificial intelligence (AI) is a branch of computer science capable of analyzing complex medical data. This can be used in diagnosis, treatment and predicting outcome in many clinical scenarios. Medicine and internet searches were carried out using the keywords ‘artificial intelligence’ and ‘neural networks’. An overview of different AI techniques is presented in this paper along with the review of importance in clinical applications. The proficiency of AI techniques has …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 8, Issue 1, 2019 · pp. 1–3 Read article
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Application of Artificial Neural Networks in Optimizing Polyhouse Roof Truss Design
Abstract: Polyhouses are specialised agricultural structures developed to maintain controlled environmental conditions for crop cultivation, thereby ensuring consistent productivity even under adverse climatic circumstances. The performance of these systems largely relies on the structural stability and cost efficiency of the roof truss, which must achieve an effective balance between strength, adaptability, and economy. In this research, an Artificial Neural Network (ANN)-based modelling framework is introduced to optimise the members of polyhouse …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 15–25 Read article
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An Aggregate-Breakage Percolation Model and ANN-Based Internal Validation for Curvature-Dependent Electrical Conductivity of MWCNT/TPU Nanocomposites
Abstract: Strain-dependent percolation models are mostly built and tested for uniaxial tension, yet many flexible sensors and stretchable devices work mainly in bending, where the outer fibre is stretched, the inner fibre is compressed and the strain changes with thickness. This study extends an aggregate-breakage percolation model, originally formulated for uniaxial strain, to through-thickness bending of a multi-walled carbon nanotube/thermoplastic polyurethane (MWCNT/TPU) nanocomposite. The local strain is taken as ε(y) = …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
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AI-Assisted Gain Scheduling for Real-Time Temperature Control in Chemical Reactors
Abstract: Temperature control in continuous stirred-tank reactors (CSTR) represents a critical challenge in chemical process industries due to inherent nonlinearities, time-varying dynamics, and parametric uncertainties. Conventional proportional-integral-derivative (PID) controllers with fixed gains often fail to maintain optimal performance across varying operating conditions, leading to temperature excursions that compromise product quality and safety. This paper presents a novel AI-assisted gain scheduling framework that integrates artificial neural networks (ANN) with adaptive PID control …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 24–33 Read article
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An AI-Driven IoT Framework for Autonomous Quality Assurance in Optical Lens Manufacturing
Abstract: The evolution of high-precision optics—ranging from smartphone micro-lenses to high-end astronomical glass—demands unprecedented accuracy in manufacturing. Traditional inspection methods, reliant on manual sampling or static automated optical inspection (AOI), often fail to bridge the gap between high-speed production and the detection of microscopic surface aberrations. This paper introduces an integrated architecture combining the Internet of Things (IoT) and Deep Learning-based decision-making systems to revolutionize lens quality control. By deploying an …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 36–41 Read article
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Autonomous Agentic AI for Adaptive Cure Optimization and Defect Prevention in Thermoset Polymer Composite Manufacturing
Abstract: Thermoset polymer composites occupy a central position in modern structural manufacturing, from aircraft fuselages to wind-turbine blades. Despite progress in resin chemistry and fiber architecture, the “cure process” that transforms compliant preforms into load-bearing structures remains difficult to manage. Manufacturers encounter ‘voids’, “interlaminar delaminations”, and “spring-back distortion” when curing complex or thick-section parts. The cause is not ignorance of the relevant physics, but rather that ‘temperature’, ‘chemistry’, ‘rheology’, and ‘mechanics’ …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 301–320 Read article
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Advancements in Machine Learning: A Comprehensive Review of Algorithms, Applications, and Future Directions
Abstract: Gaining knowledge of Machine learning (ML)-guided format algorithms leverage predictive models to generate novel devices with optimized properties across several domains, which include drug discovery, fabric synthesis, and biomolecular engineering. Selecting an effective format set of policies consists of identifying appropriate hyperparameters, predictive models, and generative mechanisms to maximize format fulfilment. This study introduces an established method for set of policies requirements, ensuring that generated designs meet predefined fulfilment criteria, …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 17–33 Read article
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Trends and Applications of Artificial Intelligence in Mechanical Engineering: A Review
Abstract: Artificial Intelligence (AI) has become a revolutionary force across various fields, including mechanical engineering, where it is redefining traditional approaches to design, manufacturing, maintenance, and overall system optimization. This review aims to provide a comprehensive introduction to AI and explore its diverse applications within the domain of mechanical engineering. The study begins with a foundational overview of AI, including key concepts such as machine learning, neural networks, deep learning, and …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 30–35 Read article
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Hand Gesture Recognition Systems: A Review of Vision-based and Sensor-based Approaches
Abstract: With many real-world uses, such as sign language translation and human-computer interaction, hand gesture detection is a crucial area of study in the science of computer vision. In this study, we propose a Convolutional Neural Network (CNN) model that uses real-time camera images to recognise hand gestures. A collection of hand motion photographs spanning the English alphabet (A-Z) was gathered, and the images were pre-processed to exclude any backdrop and …
Published in International Journal of Optical Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 15–20 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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An Intelligent Modelling system for Automotive Vehicles
Abstract: In this paper it’s about the development of artificial intelligence that has fuelled technological advancements. Self-driving automobiles are an example of an innovative development. Nowadays, you may work or sleep in your car while driving to your destination without touching the steering wheel or accelerator. This project aims to create a workable model of a self-driving car capable of traveling on multiple tracks, including curved, straight, and straight followed by …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 1, 2025 · pp. 32–40 Read article
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Artificial Neural Network Modelling to Optimize Micro-Drilling Parameters of ECDM of Developed Novel Zn/(Ag+Fe)-MMC
Abstract: Several engineering fields have increased their use of metal matrix composites (MMCs) in the past few years. Due to the increase in composites, the demand for accurate machining has also become important. Specifically, pertaining to biomaterial applications, accuracy factor with desired surface finish is critical. While the near-net shape manufacturing process has advanced, MMCs frequently require post-mould machining to achieve surface quality, and dimensional tolerances. In the present study, a …
Published in Journal of Polymer & Composites · Vol. 11, Issue 1, 2023 · pp. 01–13 Read article
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Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 1–9 Read article
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Predictive Modeling of Polymer Composites for Medical Implants Using Artificial Intelligence Techniques
Abstract: The use of polymers in biomaterials was now key to designing the next generation of medical implants, which need to be strong and also compatible with living tissue. Tests for biocompatibility, such as those done in the laboratory and by doing experiments on animals, require much time and many resources, so the need for computer-based approaches becomes clear. An artificial intelligence approach was provided in this study to determine how …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 665–692 Read article