Results 51 to 60 of about 10,511 (262)

Topological Properties of International Commodity Market: How Uncertainty Affects the Linkages?

Agribusiness, EarlyView.
ABSTRACT The study aims to explore the network topology of the international commodity market by examining the interconnections among 21 commodity futures across various categories, including energy, precious and industrial metals, and agriculture. We analyze the market structure of these commodity futures under both low and high uncertainty conditions
Ibrahim Yagli, Bayram Deviren
wiley   +1 more source

Identification of Nonlinear Systems Using the Hammerstein-Wiener Model with Improved Orthogonal Functions

Elektronika ir Elektrotechnika, 2023
Hammerstein-Wiener systems present a structure consisting of three serial cascade blocks. Two are static nonlinearities, which can be described with nonlinear functions.
Sasa S. Nikolic, Miroslav B. Milovanovic, Nikola B. Dankovic, Darko B. Mitic, Stanisa Lj. Peric, Andjela D. Djordjevic, Petar S. Djekic   +6 more
doaj   +1 more source

Identification of Non-Linear Additive Autoregressive Models

Journal of the Royal Statistical Society Series B: Statistical Methodology, 2004
SummaryWe propose a lag selection method for non-linear additive autoregressive models that is based on spline estimation and the Bayes information criterion. The additive structure of the autoregression function is used to overcome the ‘curse of dimensionality’, whereas the spline estimators effectively take into account such a structure in estimation.
Huang, Jianhua Z., Yang, Lijian
openaire   +1 more source

Nonlinear Autoregressive Conditional Duration Models for Traffic Congestion Estimation [PDF]

Journal of Probability and Statistics, 2011
The considerable impact of congestion on transportation networks is reflected by the vast amount of research papers dedicated to congestion identification, modeling, and alleviation. Despite this, the statistical characteristics of congestion, and particularly of its duration, have not been systematically studied, regardless of the fact that they can ...
Eleni I. Vlahogianni, Matthew G. Karlaftis, Konstantinos Kepaptsoglou   +2 more
openaire   +2 more sources

Does a Specialized Niche Market Vegetable Processor Enjoy Bargaining Power?

Agribusiness, EarlyView.
ABSTRACT Agribusiness companies may achieve competitive advantage through specialization within niche markets. One such niche is the fresh‐cut fruit and vegetable market, which has been steadily growing in Germany. This study examines whether the specialization of a German fresh‐cut producer grants it with market power within this niche market.
Nikolas Bublik, Franziska Mittag, Laura Hellstern, Sebastian Hess   +3 more
wiley   +1 more source

Pricing Dynamics in the US Hemp Market: A Vertical Price Transmission Analysis of the Hemp Value Chain

Agribusiness, EarlyView.
ABSTRACT The US hemp market is a new and nascent industry that has been devoid of research for about half a century. This study examined the effects of exogenous shock on price at each phase of the value chain—Farm (hemp biomass), and its impact on prices at other phases of the value chain—Intermediary Processor (crude cannabidiol hemp) and Final ...
Solomon Odiase, Tyler Mark, Patalee Buddhika Appuhamilage   +2 more
wiley   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

Historical Decompositions for Nonlinear Vector Autoregression Models [PDF]

SSRN Electronic Journal, 2017
The historical decomposition is standard within the vector autogression (VAR) toolkit. It provides an interpretation of historical fluctuations in the modelled time series through the lens of the identified structural shocks. The proliferation of nonlinear VAR models naturally leads to extending the historical decomposition into nonlinear settings ...
openaire   +1 more source