On the Space-Time Correlation of Heat Release Rate in Turbulent Premixed Flames

Liu, Yu

doi:10.1080/00102202.2015.1085861

Cited by 1 publication

(1 citation statement)

References 52 publications

(72 reference statements)

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“…Meanwhile, Zaburdaev et al (2013) proposed a space-time velocity correlation function for random walks. Liu (2016) subsequently developed a space-time correlation function related to the heat release rate in turbulent premixed flames. These models are primarily intended for use in physics and chemistry applications rather than the social sciences or economics; as such, they, too, are difficult to understand.…”

Section: Literature Review and Model Designmentioning

confidence: 99%

Dynamic spatiotemporal correlation coefficient based on adaptive weight

Tan

Zhang

et al. 2023

Financ Innov

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Risk management is an important aspect of financial research because correlations among financial data are essential in evaluating portfolio risk. Among various correlations, spatiotemporal correlations involve economic entity attributes and are interrelated in space and time. Such correlations have therefore drawn increasing attention in financial risk management. However, classical correlation measurements are typically based on either time series correlations or spatial dependence; they cannot be directly applied to financial data with spatiotemporal correlations. The spatiotemporal correlation coefficient model with adaptive weight proposed in this paper can (1) address the absolute quantity, dynamic quantity, and dynamic development of financial data and (2) be used for risk grading, financial risk evaluation, and portfolio management. To verify the validity and superiority of this model, cluster analysis results and portfolio performance are compared with a classical model with time series correlation or spatial correlation, respectively. Empirical findings show that the proposed coefficient is highly effective and convenient compared to others. Overall, our method provides a highly efficient financial risk management method with valuable implications for investors and financial institutions.

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Section: Literature Review and Model Designmentioning

confidence: 99%