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627 articles for “neural”
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VolleyNexis AI: A Multimodal Artificial Intelligence Framework for Opponent Strategy Prediction, Tactical Intelligence, and Athlete Performance Optimization in Volleyball
Abstract: The rapid advancement of Artificial Intelligence (AI) has profoundly transformed sports analytics, enabling deeper insights, real-time data analysis, and enhanced performance predictions. Noticeable results have been seen by enabling automated analysis of complex gameplay patterns along with athlete performance. Volleyball is a dynamic and strategic sport, which requires continuous tactical adjustments and constant monitoring of the player’s performance. This paper presents VolleyNexis AI, which is a multimodal artificial intelligence framework …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 2, 2025 Read article
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Computational Intelligence and Neuro-Fuzzy Modelling of Polymer Composites: A Critical Review of Performance Prediction and Optimization
Abstract: The increased variety in polymer matrices, reinforcements, fillers, and processing parameters has led to the need to better understand the structure-property, process-property relationships in order to accurately predict and optimize the performance of polymer composites. This paper reviews the applications of computational intelligence methods in polymer composites, with special focus on artificial neural networks, adaptive neuro-fuzzy inference systems, machine learning techniques, and hybrid optimization. The literature is analyzed based on …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Artificial Intelligence and Constitutive Modeling Equations for Predictive Design of High-Performance Polymer Composites
Abstract: Growing polymer composite applications demand accurate mechanical prediction, yet complex interactions and conventional constitutive models limit predictive capability and require extensive calibration. To report these challenges, this research recommends a combined Artificial Intelligence (AI) and constitutive modeling approach based on an Enhanced Tasmanian Devil Optimizer-tuned Residual Neural Network with Multilayer Perceptron (ETDO-ResNet-MLP) for the predictive design of high-performance polymer composites. The study uses a publicly available Polymer Composite Property Dataset …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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AI-Assisted Kinetic Modeling of PLA Hydrolysis Under Subcritical Water Conditions for Sustainable Polymer Recycling
Abstract: The accumulation of poly (lactic acid) (PLA) in terrestrial and marine ecosystems has intensified the demand for closed-loop, green recycling technologies. Subcritical water (SCW) hydrolysis offers a promising, catalyst-free pathway for the rapid depolymerization of PLA into its constituent monomer, lactic acid. However, the complex, highly non-linear kinetics governing macro-molecular degradation under variable hydrothermal conditions limit real-time process optimization and industrial scalability. This study develops a novel artificial intelligence (AI)-assisted …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 2, 2026 · pp. 65–74 Read article
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Deep Learning for Earth Observation Using Satellite Imagery: A Comprehensive Review
Abstract: Earth observation (EO) satellites provide continuous, large-scale information about the Earth's land, oceans, atmosphere, vegetation, infrastructure, and environmental conditions. The rapid growth of multispectral, hyperspectral, synthetic aperture radar (SAR), thermal, and high- resolution satellite missions has generated large volumes of heterogeneous spatial and temporal data. Conventional image-processing and machine-learning techniques often require manually designed features and may have difficulty representing the complex spatial, spectral, temporal, and multimodal characteristics of satellite …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article
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Harnessing Artificial Intelligence for Precision Physics: A Machine Learning Framework for Data Reconstruction in Support of India's Deep-Tech Missions
Abstract: India's emergence as a global leader in deep-tech innovation is driven by ambitious scientific megaprojects, including the Laser Interferometer Gravitational-Wave Observatory (LIGO)-India, the X-ray Polarimeter Satellite (XPoSat), the Aditya-L1 solar observatory, and the National Quantum Mission (NQM). However, the unprecedented scale and complexity of the observational data generated by these missions present severe computational bottlenecks. Traditional analytical frameworks struggle with non-stationary noise transients, diffusion blurring, and the exponential scaling limits …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 2, 2026 · pp. 48–55 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