2022 Annual Meeting

Session: Interactive Session: Data and Information Systems

Chair

Kwon, J., Texas A&M University

Co-Chairs

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

Presentations

03:30 PM

(362u) High-Throughput Screening for Identifying Potential Chemical Exposure Scenarios at End-of-Life Stage
Hernandez-Betancur, J., Ruiz-Mercado, G., Martin, M.
(362ab) Digitalization of an Experimental Electrochemical Reactor Via the Smart Manufacturing Innovation Platform
Luo, J., Citmaci, B., Korambath, P., Jang, J., Morales-Guio, C., Davis, J., Christofides, P.
(362k) Accurate Surrogate Models for Stochastic Simulations Using Parin: Parameter As Input-Variable
Mohammadi, S., Cremaschi, S.
(362l) Cost Optimization of Steel Alloying Elements with Machine Learning Based Jominy Hardness Profile Prediction
Allen, L., Moghadam, P. Z., Cordiner, J.
(362aa) Process Monitoring and Online Fault Detection and Diagnosis Using Deep Recurrent Neural Networks on Plant Data
Yerimah, L. E., Ghosh, S., Wang, Y., Cao, Y., Flores-Cerrillo, J., Bequette, B. W.
(362v) Experimental Evaluation of the Level Detection in Separators Using Electrical Tomography
Nissinen, A., Voutilainen, A., Kaunisto, P., Vänskä, J., Tienhaara, M.
(362r) Modeling Dynamics of Material Flows in Coupled Industrial Processes Using Data Driven System Identification
Farlessyost, W., Singh, S.
(362w) Cover Cut Based Algorithm for Optimal Sensor Network Design
Magbool Jan, N., M, A.
(362x) Ensemble Learning for Fault Diagnosis in Chemical Processes: Fusion of Results through a K-Nearest Neighbors Algorithm
Sai Vasista, B., Srinivasan, R.
(362e) A Comparative Evaluation of Machine Learning Algorithms in Predicting Syngas Fermentation Outcomes Using Limited Experimental Data
Roell, G., Wan, N., Sathish, A., Wen, Z., Tang, Y., Bao, F. S.
(362f) Development of Bayesian Machine Learning Algorithms for Optimal Nonlinear Model Selection and Parameter Estimation from Noisy Data of Unknown Characteristics
Adeyemo, S., Bhattacharyya, D.
(362p) Data-Driven Modeling of Complex Nonlinear Systems Using Hybrid Series and Parallel Nonlinear Static – Dynamic Stochastic Neural Networks
Mukherjee, A., Bhattacharyya, D.
(362g) Soft Actor-Critic Deep Reinforcement Learning with Hybrid Actions for Scheduling of Energy Systems Under Demand Response
Campos, G., El-Farra, N., Palazoglu, A.
(362q) Multi-Rate Data-Driven Models for Lactic Acid Fermentation - Parameter Identification and Prediction
Parulekar, S., Gan, J.
(362h) Physics Informed Machine Learning for Feasibility Analysis
Kilwein, Z., Eydenberg, M., Blakely, L., Boukouvala, F.
(362i) Virtual Sample Generation Based on Quantile Regression Variational Generative Adversarial Network for Soft-Sensing Modeling
Zhang, X., Zhu, Q., Yin, X.
(362ac) Physics-Based Penalization for Hyperparameter Optimization in Gaussian Process Regression
Boukouvala, F., Kim, J., Paynabar, K., Luettgen, C. O.
(362j) Rnn and Transfer Learning for Battery Life Prediction of Electric Vehicles Based on Real-Road Driving Obd Data and Lab Measurements
Lim, J., Shin, D., Jang, D., Lee, J.
(362y) Failure Stage Classification and Its Application to Predicting Remaining Useful Life of Bearings
Hassani, B., He, Q. P.
(362b) Multi-objective Optimization of Process Efficiency and CO2 Emission for On-Site Hydrogen Production Process Using Hybrid Data-Driven Model.
Lee, J., Hong, S., Cho, H., Ga, S., Kim, J.
(362a) A Reinforcement Learning Approach for Stochastic Cutting Stock Problem
Su, J. Y., Kang, J. L., Jang, S. S.
(362s) Developing Risk Assessment Framework for Wildfire in the United States – a Deep Learning Approach
Hu, P., Wang, Q., Zhang, Z.
(362m) Hybrid, Interpretable Machine Learning for Thermodynamic Property Estimation Using Grammar2vec for Molecular Representation
Mann, V., Brito, K., Gani, R., Venkatasubramanian, V.
(362z) Root Cause Identification Using Cross-Correlation Weighted Lag in Chemical Plants
Bansal, A., Mankodi, N., Ullah, M. F., Suresh, R., Rengaswamy, R.
(362n) Predicting Activity Coefficients at Infinite Dilution Using Hybrid Residual Graph Neural Networks
Sanchez Medina, E. I., Linke, S., Sundmacher, K., Stoll, M.
(362o) Improved Performance of Artificial Neural Networks Via Hyperparameter Optimization and Data Augmentation for a Small Number of Data Sets
Lim, Y. I., Jung, P. G.