255 Advances in Data Analysis, Information Management, and Intelligent Systems I


Description:
Advanced sensing communications technologies and are increasing the amount and variety of data available to monitor chemical processes. This session will cover analytics techniques to translate Big Data into actionable insights - such as: improve product quality, productivity and yield and save money. This session welcomes both methodological contributions as well as industrial practitioner case studies.

Sponsor:
Data and Information Systems


Chair:
Fani Boukouvala
Assistant Professor
Georgia Institute of Technology
School of Chemical and Biomolecular Engineering
Atlanta, GA
77843
Email: fani.boukouvala@chbe.gatech.edu

Co-Chair:
Franjo Cecelja
Proffesor
University of Surrey
Process and Information Systems Engineering Research Centre
University of Surrey
Guildford
GU2 7UH
Email: f.cecelja@surrey.ac.uk


Papers:
255a
Comparison of Machine Learning Approaches for Process Model Development from Big Data
Sarah Davis, Auburn University; Selen Cremaschi, Auburn University; Mario Richard Eden, Auburn University
255b
Application of Machine Learning Algorithms for the Selection of Jet Fuel from Hydrocarbon Blends
Rajib Mukherjee, Gas and Fuels Research Center, Texas A&M Engineering Experiment Station; Noof Abdalla, Texas A&M Qatar; Nasr Mohamed, Texas A&M Qatar; Marwan El Wahsh, Texas A&M University at Qatar; Nimir Elbashir, Texas A&M University at Qatar; Mahmoud M. El-Halwagi, Texas A&M University
Break
255d
Determination of the Optimal Number of Eigenfunctions in Proper Orthogonal Decomposition Based on Machine Learning
Harwinder Singh Sidhu, Texas A&M University; Abhinav Narasingam, Texas A&M University; Prashanth Siddhamshetty, Texas A&M Energy Institute, Texas A&M University; Joseph Sangil Kwon, Texas A&M University
255e
A Scalable Statistical Machine Learning Method: Application for Fault Detection and Fault Propagation Pattern Inference in the Tennessee Eastman Process
Taha Mohseni Ahooyi, Temple University; Jeffrey E. Arbogast, Process Control & Logistics, Air Liquide; Masoud Soroush, Drexel University
255f
Decision Support Platform for the Automation of Processing Recipes and Process Scheduling Management Supported By Knowledge Management
Elisabet Capón-García, ETH Zurich; Edrisi Muñoz, Centro de Investigacion en Matematicas A.C.; Luis Puigjaner, Universitat Politècnica de Catalunya
255g
Machine Learning Based Uncertainty Quantification of Erosion in Pipeline Transportation
Wei Dai, Auburn University; Selen Cremaschi, Auburn University
255h
Generating Ontology-Based Process Models Automatically
Arne Tobias Elve, Norwegian University of Science and Technology (NTNU); Heinz A. Preisig, Norwegian University of Science and Technology (NTNU)
Abstract Submissions Closed
See more of this Group/Topical: Computing and Systems Technology Division
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