Results 71 to 80 of about 874,187 (329)
ARTIFICIAL NEURAL NETWORK FOR MODELS OF HUMAN OPERATOR
Acta Polytechnica CTU Proceedings, 2017 This paper presents a new approach to mental functions modeling with the use of artificial neural networks. The artificial neural networks seems to be a promising method for the modeling of a human operator because the architecture of the ANN is directly
Martin Ruzek
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Advanced Engineering Materials, EarlyView.In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi +4 more
wiley +1 more source
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
Advanced Engineering Materials, EarlyView.This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source
Training a Feed-forward Neural Network with Artificial Bee Colony Based Backpropagation Method
, 2012 Back-propagation algorithm is one of the most widely used and popular techniques to optimize the feed forward neural network training. Nature inspired meta-heuristic algorithms also provide derivative-free solution to optimize complex problem. Artificial
Das, Achintya +2 more
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Advancing Wildfire‐Retardant Materials: Engineering Strategies for Direct and Indirect Suppression
Advanced Engineering Materials, EarlyView.Here, the evolution, ecological impact, and performance of current fire‐retardant materials and suppression strategies are reviewed, offering an engineering perspective to address existing challenges and propose pathways for the development of more effective, scalable, and sustainable solutions to meet the demands of a changing climate. Wildfires cause
Changxin Dong +4 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Additive manufacturing (AM) transforms space hardware by enabling lightweight, high‐performance, and on‐demand production. This review outlines AM processes—powder bed fusion (PBF), directed energy deposition (DED), binder jetting (BJ), sheet lamination (SL), and material extrusion (ME)—applied to propulsion, satellite structures, and thermal devices ...
Stelios K. Georgantzinos +8 more
wiley +1 more source
Developing Artificial Neural Network Based on Visual Studio for Dance Assessment
Jurnal Pendidikan Teknologi dan Kejuruan, 2017 The dance assessment test still uses a manual system that tend to have frequent errors in the calculation for the final results thus it requires a system that accelerate the assessment process with an accurate result.
Febri Suci Rahmahwati, Fatchul Arifin
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Bioinspired Materials, Designs, and Manufacturing Strategies for Advanced Impact‐Resistant Helmets
Advanced Engineering Materials, EarlyView.This review explores how bioinspired materials, structures, and manufacturing strategies transform helmet design to achieve enhanced impact resistance. Drawing inspiration from nacre, porcupine quills, beetle exoskeletons, and skull architectures, it highlights advances in auxetic lattices, nanocomposites, and functionally graded foams.
Joseph Schlager +4 more
wiley +1 more source
Energy Efficiency Prediction using Artificial Neural Network [PDF]
, 2019 Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important,
Abu-Naser, Samy S. +4 more
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