Data-Driven Analysis of Nonlinear Heterogeneous Reactions through Sparse Modeling and Bayesian Statistical Approaches

Data-Driven Analysis of Nonlinear Heterogeneous Reactions through Sparse Modeling and Bayesian Statistical Approaches

Heterogeneous reactions are chemical reactions that occur at the interfaces of multiple phases, and often show a nonlinear dynamical behavior due to the effect of the time-variant surface area with complex reaction mechanisms. It is important to specify the kinetics of heterogeneous reactions in ord...

Full description

Bibliographic Details
Main Authors: Masaki Ito, Tatsu Kuwatani, Ryosuke Oyanagi, Toshiaki Omori
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Entropy
Subjects:
sparse modeling
sequential Monte Carlo method
time series data analysis
heterogeneous reactions
Online Access:https://www.mdpi.com/1099-4300/23/7/824

Internet

https://www.mdpi.com/1099-4300/23/7/824

Similar Items