Results 51 to 60 of about 25,591 (263)
Ekonomska Misao i Praksa, 2017 This paper investigates the concept and estimation of the output gap in transition economies, with special reference to the Czech Republic, Estonia and Kosovo.
Albulenë Kastrati +2 more
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Advanced Engineering Materials, EarlyView.Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter +10 more
wiley +1 more source
A Note on ‘What Drives Share Prices in the Middle East?’
The International Journal of Banking and Finance, 2008 There are several hypotheses suggesting that some properties of oil prices make it interesting to focus on the predictive ability of oil prices for stock returns.
Panos Priftakis, M. Ishaq Bhatti
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Tropical Agricultural Research, 2015 Forecasting a time series is generally done by using autoregressive integrated moving average (ARIMA) models. The main drawback of this technique is that the time series should be stationary. In reality, this assumption is rarely met.
N.K.K. Brintha +4 more
doaj +1 more source
On the identification of multivariate correlated unobserved components models [PDF]
Economics Letters, 2016 This paper analyses identification for multivariate unobserved components models in which the innovations to trend and cycle are correlated. We address order and rank criteria as well as potential non-uniqueness of the reduced-form VARMA model. Identification is shown for lag lengths larger than one in case of a diagonal vector autoregressive cycle.
Trenkler, Carsten, Weber, Enzo
openaire +3 more sources
Advanced Engineering Materials, EarlyView.This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani +7 more
wiley +1 more source
Nominal stability over two centuries
Swiss Journal of Economics and Statistics, 2019 I assess the stability of the monetary environment in Switzerland over the past two centuries. In order to control for transitory measurement errors, in particular in nineteenth century data, I use an unobserved-components stochastic-volatility model to ...
Daniel Kaufmann
doaj +1 more source
Dynamic generalised additive models (DGAMs) for forecasting discrete ecological time series
Methods in Ecology and Evolution, 2023 Generalised additive models (GAMs) are increasingly popular tools for estimating smooth nonlinear relationships between predictors and response variables.
Nicholas J. Clark, Konstans Wells
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Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning
Advanced Engineering Materials, EarlyView.Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose +7 more
wiley +1 more source
Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery
Advanced Functional Materials, EarlyView.Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang +3 more
wiley +1 more source