2022 Annual Meeting

Session: Data Science/Analytics for Process Applications

Chair

Ellis, M., University of California, Davis

Co-Chair

Presentations

03:30 PM

(185a) Data Fusion and Feature Selection for Process Monitoring at Hanford

03:49 PM

(185b) A Comprehensive Causation Prediction Model of Pipeline Incidents Using Artificial Neural Network

04:08 PM

(185c) Data-Driven Feasibility and Performance Prediction of Production Scheduling MIP Models

04:27 PM

(185d) Machine Learning-Based Operational Modeling of an Electrochemical Reactor: Handling Data Variability and Improving Empirical Models

04:46 PM

(185e) A Graph-Based Software Framework for Data Science

05:05 PM

(185f) Machine Learning-Based Ethylene Concentration Estimation, Real-Time Optimization and Feedback Control of an Experimental Electrochemical Reactor

05:24 PM

(185g) Optimization Methods for Exploring Accuracy Versus Robustness of a Regression Prediction in Process Analytical Technology

05:43 PM

(185h) Data-Driven Techniques Towards the Efficient Integration of Planning, Scheduling and Control