Results 101 to 110 of about 270,750 (256)
The Prediction of Soil Bearing Capacity Using Error Root Mean Square [PDF]
Proceedings of the 2nd International Conference on Industrial and Technology and Information Design, ICITID 2021, 30 August 2021, Yogyakarta, Indonesia, 2021 Ridayati Ridayati, Anggi Hermawan
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dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
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Interpolatory model reduction of dynamical systems with root mean squared error
IFAC-PapersOnLineThe root mean squared error is an important measure used in a variety of applications such as structural dynamics and acoustics to model averaged deviations from standard behavior. For large-scale systems, simulations of this quantity quickly become computationally prohibitive.
Reiter, Sean, Werner, Steffen W. R.
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Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
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Advanced Engineering Materials, EarlyView.A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
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Advanced Engineering Materials, EarlyView.This study examines how helicoidal architectures with different porosities respond to bending. Adjusting layer angle and spacing in 3D‐printed polymers reveals clear tradeoffs between stiffness, strength, and energy absorption. Experiments and simulations highlight designs that distribute stress effectively, offering pathways for optimizing lightweight
Praveenkumar Subhash Patil +2 more
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PLoS ONEDemand forecasting is a quite challenging task, which is sensitive to several factors such as endogenous and exogenous parameters. In the context of supply chain management, demand forecasting aids to optimize the resources effectively.
Mohamed Irhuma +3 more
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Advanced Engineering Materials, EarlyView.Postbuild annealing systematically modifies the phase fractions and morphology of EB‐PBF processed Mo–9Si–8B. Quantitative microstructure–property correlations reveal how controlled phase evolution enhances high‐temperature compressive strength and creep resistance.
Christopher Schmidt +5 more
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JTAM (Jurnal Teori dan Aplikasi Matematika)Neural Network (NN) is an information processing system that has characteristics similar to biological neural networks. One of the algorithms in NN is Backpropagation Neural Network (BPNN).
Mislan Mislan, Andrea Tri Rian Dani
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Advanced Engineering Materials, EarlyView.Sustainability assessment requires methodologies that appropriately distinguish between additive and non‐additive material properties. A toxicity‐weighted scoring system is developed and applied that accounts for the disproportionate influence of highly toxic constituents through nonlinear weighting functions, providing more realistic estimates than ...
Seth Mehalic +2 more
wiley +1 more source