Optimal Nonlinear Dynamic Sparse Model Selection and Bayesian Parameter Estimation for Nonlinear Systems

Data-based modeling and control of nonlinear process systems using sparse identification: An overview of recent results

(2023) Fahim Abdullah et al.   COMPUTERS & CHEMICAL ENGINEERING

Perspectives on the Integration between First-Principles and Data-Driven Modeling

(2022) William Bradley et al.   COMPUTERS & CHEMICAL ENGINEERING

Modeling and Control of Nonlinear Processes Using Sparse Identification: Using Dropout to Handle Noisy Data

(2022) Fahim Abdullah et al.   Industrial & Engineering Chemistry Research

Recent trends on hybrid modeling for Industry 4.0

(2021) Joel Sansana et al.   COMPUTERS & CHEMICAL ENGINEERING

Risk-based fault prediction of chemical processes using operable adaptive sparse identification of systems (OASIS)

(2021) Bhavana Bhadriraju et al.   COMPUTERS & CHEMICAL ENGINEERING

Handling noisy data in sparse model identification using subsampling and co-teaching

(2021) Fahim Abdullah et al.   COMPUTERS & CHEMICAL ENGINEERING

Sparse-identification-based model predictive control of nonlinear two-time-scale processes

(2021) Fahim Abdullah et al.   COMPUTERS & CHEMICAL ENGINEERING

OASIS-P: Operable Adaptive Sparse Identification of Systems for fault Prognosis of chemical processes

(2021) Bhavana Bhadriraju et al.   JOURNAL OF PROCESS CONTROL

Operable adaptive sparse identification of systems (OASIS): application to chemical processes

(2020) Bhavana Bhadriraju et al.   AICHE JOURNAL

ALVEN: Algebraic learning via elastic net for static and dynamic nonlinear model identification

(2020) Weike Sun et al.   COMPUTERS & CHEMICAL ENGINEERING

Overview of Surrogate Modeling in Chemical Process Engineering

(2019) Kevin McBride et al.   CHEMIE INGENIEUR TECHNIK

Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO2 Capture Using Pilot-Plant Data

(2019) Anderson Soares Chinen et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Introductory overview of identifiability analysis: A guide to evaluating whether you have the right type of data for your modeling purpose

(2019) Joseph H.A. Guillaume et al.   ENVIRONMENTAL MODELLING & SOFTWARE

Incorporating Parameter Estimability Into Model Selection

(2019) Jake M. Ferguson et al.   Frontiers in Ecology and Evolution

Advances in surrogate based modeling, feasibility analysis, and optimization: A review

(2018) Atharv Bhosekar et al.   COMPUTERS & CHEMICAL ENGINEERING

Development of a Rigorous Modeling Framework for Solvent-Based CO2 Capture. Part 2: Steady-State Validation and Uncertainty Quantification with Pilot Plant Data

(2018) Joshua C. Morgan et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Constrained sparse Galerkin regression

(2018) Jean-Christophe Loiseau et al.   JOURNAL OF FLUID MECHANICS

The promise of artificial intelligence in chemical engineering: Is it here, finally?

(2018) Venkat Venkatasubramanian   AICHE JOURNAL

Exploiting connectivity structures for decomposing process plants

(2018) Temitayo Bankole et al.   JOURNAL OF PROCESS CONTROL

Robust identification for nonlinear errors-in-variables systems using the EM algorithm

(2017) F. Guo et al.   JOURNAL OF PROCESS CONTROL

Discovering governing equations from data by sparse identification of nonlinear dynamical systems

(2016) Steven L. Brunton et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Uncertainty quantification of property models: Methodology and its application to CO2 -loaded aqueous MEA solutions

(2015) Joshua C. Morgan et al.   AICHE JOURNAL

A combined first-principles and data-driven approach to model building

(2015) Alison Cozad et al.   COMPUTERS & CHEMICAL ENGINEERING

Learning surrogate models for simulation-based optimization

(2014) Alison Cozad et al.   AICHE JOURNAL

Plant-wide control system design: Primary controlled variable selection

(2014) Dustin Jones et al.   COMPUTERS & CHEMICAL ENGINEERING

On kalman filter for linear system with colored measurement noise

(2014) Guobin Chang   JOURNAL OF GEODESY

Data mining with big data

(2013) Xindong Wu et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

The online use of first-principles models in process operations: Review, current status and future needs

(2012) C.C. Pantelides et al.   COMPUTERS & CHEMICAL ENGINEERING

Dynamic Data-Driven Modeling of Pharmaceutical Processes

(2011) F. Boukouvala et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

System identification of nonlinear state-space models

(2010) Thomas B. Schön et al.   AUTOMATICA

Fundamental Limit of Sample Generalized Eigenvalue Based Detection of Signals in Noise Using Relatively Few Signal-Bearing and Noise-Only Samples

(2010) Raj Rao Nadakuditi et al.   IEEE Journal of Selected Topics in Signal Processing

Robust identification of piecewise/switching autoregressive exogenous process

(2009) Xing Jin et al.   AICHE JOURNAL

A particle filter approach to identification of nonlinear processes under missing observations

(2009) R. B. Gopaluni   CANADIAN JOURNAL OF CHEMICAL ENGINEERING