Results 71 to 80 of about 188,817 (310)
Advanced Engineering Materials, EarlyView.This study shows that superalloys used in aircraft engine disks become much more prone to deformation at high temperatures if they have been strained during manufacturing. This effect increases with the level of prior strain but eventually reaches a limit.
Fabio Machado Alves da Fonseca +9 more
wiley +1 more source
Strong Approximations for Nonlinear Transformations of Integrated Time Series [PDF]
In this paper we establish the strong approximations for the nonlinear transformations of integrated time series. Both the asymptotically homogeneous and integrable transformations are considered, and the explicit rates for the convergence to their limit
Park, Joon
core
Advanced Engineering Materials, EarlyView.This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
Advanced Functional Materials, EarlyView.ABSTRACT Electronic waste has emerged as a major environmental challenge, driven by the massive consumption and a limited lifetime of modern electronic devices, stimulating the development of sustainable electronics. Here, an all‐biomaterial gelatin‐choline‐citric acid ([Ch][CA]) ionogel is developed as an active binder to realize self‐sintered ...
Lin Guo +10 more
wiley +1 more source
Multi-step learning rule for recurrent neural models: an application to time series forecasting [PDF]
, 2001 Multi-step prediction is a difficult task that has attracted increasing interest in recent years. It tries to achieve predictions several steps ahead into the future starting from current information.
Galván, Inés M. +3 more
core +1 more source
Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites
Advanced Functional Materials, EarlyView.A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou +5 more
wiley +1 more source
Local-global neural networks: a new approach for nonlinear time series modelling [PDF]
In this paper, the Local Global Neural Networks model is proposed within the context of time series models. This formulation encompasses some already existing nonlinear models and also admits the Mixture of Experts approach.
Marcelo C. Medeiros +2 more
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Advanced Functional Materials, EarlyView.Field‐free spin‐orbit torque domain‐wall synapses integrated with stochastic MTJ neurons enable compact hardware Boltzmann machines. Leveraging intrinsic stochasticity and multi‐level conductance, the system achieves efficient probabilistic learning with high accuracy, demonstrating a scalable spintronic platform for energy‐efficient edge AI.
Aijaz H. Lone +8 more
wiley +1 more source
Revista Colombiana de Estadística, 2005 In the literature on time series analysis it has been established in recent years that the hydrological/meteorological time series are well described by nonlinear models, in particular by the SETAR (Self- exciting threshold autoregressive) models.
Briñez Ángela P., Nieto Fabio H.
doaj
Mutual information: a dependence measure for nonlinear time series [PDF]
This paper investigates the possibility to analyse the structure of unconditional or conditional (and possibly nonlinear) dependence in financial returns without requiring the specification of mean-variance models or a theoretical probability ...
Andreia Dionisio +2 more
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