Results 91 to 100 of about 3,569 (224)
This study shows that integrating multiple machine learning models with optimization and decision‐making improves chemical process design, and that a consensus‐based strategy across models provides more robust and reliable operating recommendations than any single model, especially under limited or noisy data conditions.
Farough Agin +2 more
wiley +1 more source
ABSTRACT The leading‐order asymptotic behavior of the solution of the Cauchy initial‐value problem for the Benjamin–Ono equation in L2(R)$L^2(\mathbb {R})$ is obtained explicitly for generic rational initial data u0$u_0$. An explicit asymptotic wave profile uZD(t,x;ε)$u^\mathrm{ZD}(t,x;\epsilon)$ is given, in terms of the branches of the multivalued ...
Elliot Blackstone +3 more
wiley +1 more source
Studies using climatic gradients play a key role in our understanding of the importance of rainfall and temperature as factors regulating species diversity and distribution, and thus of likely responses to climate change. However, such studies currently consider above‐ground species only, ignoring the diverse hypogaeic (subterranean) invertebrate fauna.
François Brassard +3 more
wiley +1 more source
Seismic Structural Reliability by Time‐Variant Fragility Functions
ABSTRACT The seismic vulnerability of aging structures is often represented in the form of fragility curves that vary with time. On one hand, each of these functions is intended to apply if the earthquake hits at the time the fragility refers to. On the other hand, performance‐based earthquake engineering (PBEE) resources to classical probabilistic ...
Iunio Iervolino
wiley +1 more source
Intraday Functional PCA Forecasting of Cryptocurrency Returns
ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley +1 more source
The Impact of Uncertainty on Forecasting the US Economy
ABSTRACT This paper examines the predictive value of uncertainty measures for key macroeconomic indicators across multiple forecast horizons. We evaluate how different uncertainty proxies—economic policy uncertainty (EPU), VIX, geopolitical risk, and measures of macroeconomic and financial uncertainty—enhance forecast accuracy for industrial production,
Angelica Ghiselli
wiley +1 more source
Using DSGE and Machine Learning to Forecast Public Debt for France
ABSTRACT Forecasting public debt is essential for effective policymaking and economic stability, yet traditional approaches face challenges due to data scarcity. While machine learning (ML) has demonstrated success in financial forecasting, its application to macroeconomic forecasting remains underexplored, hindered by short historical time series and ...
Emmanouil Sofianos +4 more
wiley +1 more source
Embracing Complexity in HRM Research: A Call for System and Process Perspectives
ABSTRACT Human resource management (HRM) is inherently complex. It involves systems of principles, practices, and activities operating at individual, group, organizational, and macro levels, which are interlinked through complex processes. Yet, empirical research has not kept pace with this conceptual richness.
Rebecca Hewett, Madleen Meier‐Barthold
wiley +1 more source
Motive and Opportunity: Order Choice in a Limit Order Book With Dispersed Information
ABSTRACT We test predictions of market microstructure theory relating to the determinants of order choice in a limit order book where information is dispersed among traders. Using an experimental limit order book, with a large state space, we find that informed traders exhibit patience, compatible with the ‘waiting game’ behaviour described in Foster ...
James Steeley +2 more
wiley +1 more source
Artificial intelligence–driven decoupling structure–activity relationship for lithium‐ion batteries
Artificial intelligence can efferently accelerate the high‐throughput screening of battery materials, the analysis of multiphase mechanisms, and the precise prediction of capacity and cycle life. This review systematically summarizes the applications of machine learning (ML) in decoupling the complex structure‐activity relationships of lithium‐ion ...
Tao Wang +6 more
wiley +1 more source

