Interactive Session: Data and Information Systems | AIChE

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Interactive Session: Data and Information Systems

Chair(s)

Kwon, J., Texas A&M University

Co-chair(s)

Dubljevic, S., University of Alberta
Chen, Y., University of Wisconsin-Madison, Department of Che
Xie, J., University of Alberta

This session solicits posters in the broad area of Data and Information Management in the chemical engineering domain. Abstracts describing methods, applications, challenges, and tools are all welcome.

Presentations

3:30 PM
(362n) Predicting Activity Coefficients at Infinite Dilution Using Hybrid Residual Graph Neural Networks
3:30 PM
(362r) Modeling Dynamics of Material Flows in Coupled Industrial Processes Using Data Driven System Identification
3:30 PM
(362h) Physics Informed Machine Learning for Feasibility Analysis
3:30 PM
(362s) Developing Risk Assessment Framework for Wildfire in the United States – a Deep Learning Approach
3:30 PM
(362l) Cost Optimization of Steel Alloying Elements with Machine Learning Based Jominy Hardness Profile Prediction
3:30 PM
(362p) Data-Driven Modeling of Complex Nonlinear Systems Using Hybrid Series and Parallel Nonlinear Static – Dynamic Stochastic Neural Networks
3:30 PM
(362b) Multi-objective Optimization of Process Efficiency and CO2 Emission for On-Site Hydrogen Production Process Using Hybrid Data-Driven Model.
3:30 PM
(362u) High-Throughput Screening for Identifying Potential Chemical Exposure Scenarios at End-of-Life Stage
3:30 PM
(362x) Ensemble Learning for Fault Diagnosis in Chemical Processes: Fusion of Results through a K-Nearest Neighbors Algorithm
3:30 PM
(362ac) Physics-Based Penalization for Hyperparameter Optimization in Gaussian Process Regression
3:30 PM
(362z) Root Cause Identification Using Cross-Correlation Weighted Lag in Chemical Plants
3:30 PM
(362v) Experimental Evaluation of the Level Detection in Separators Using Electrical Tomography
3:30 PM
(362q) Multi-Rate Data-Driven Models for Lactic Acid Fermentation - Parameter Identification and Prediction
3:30 PM
(362k) Accurate Surrogate Models for Stochastic Simulations Using Parin: Parameter As Input-Variable
3:30 PM
(362f) Development of Bayesian Machine Learning Algorithms for Optimal Nonlinear Model Selection and Parameter Estimation from Noisy Data of Unknown Characteristics
3:30 PM
(362y) Failure Stage Classification and Its Application to Predicting Remaining Useful Life of Bearings
3:30 PM
(362o) Improved Performance of Artificial Neural Networks Via Hyperparameter Optimization and Data Augmentation for a Small Number of Data Sets
3:30 PM
(362w) Cover Cut Based Algorithm for Optimal Sensor Network Design
3:30 PM
(362i) Virtual Sample Generation Based on Quantile Regression Variational Generative Adversarial Network for Soft-Sensing Modeling
3:30 PM
(362a) A Reinforcement Learning Approach for Stochastic Cutting Stock Problem
3:30 PM
(362m) Hybrid, Interpretable Machine Learning for Thermodynamic Property Estimation Using Grammar2vec for Molecular Representation
3:30 PM
(362aa) Process Monitoring and Online Fault Detection and Diagnosis Using Deep Recurrent Neural Networks on Plant Data
3:30 PM
(362g) Soft Actor-Critic Deep Reinforcement Learning with Hybrid Actions for Scheduling of Energy Systems Under Demand Response
3:30 PM
(362ab) Digitalization of an Experimental Electrochemical Reactor Via the Smart Manufacturing Innovation Platform
3:30 PM
(362e) A Comparative Evaluation of Machine Learning Algorithms in Predicting Syngas Fermentation Outcomes Using Limited Experimental Data
3:30 PM
(362j) Rnn and Transfer Learning for Battery Life Prediction of Electric Vehicles Based on Real-Road Driving Obd Data and Lab Measurements

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Individuals

AIChE Pro Members $150.00
AIChE Emeritus Members $105.00
AIChE Graduate Student Members Free
AIChE Undergraduate Student Members Free
AIChE Explorer Members $225.00
Non-Members $225.00

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