2022 Annual Meeting

Session: Interactive Session: Data and Information Systems

Chair

Joseph Kwon, Texas A&M University

Co-Chairs

Stevan Dubljevic, University of Alberta
Yifu Chen, University of Wisconsin-Madison, Department of Che
Junyao Xie, University of Alberta

Presentations

03:30 PM

(362x) Ensemble Learning for Fault Diagnosis in Chemical Processes: Fusion of Results through a K-Nearest Neighbors Algorithm
Bairi Sai Vasista, Rajagopalan Srinivasan
(362a) A Reinforcement Learning Approach for Stochastic Cutting Stock Problem
Jie-Ying Su, Jia-Lin Kang, Shi-Shang Jang
(362b) Multi-objective Optimization of Process Efficiency and CO2 Emission for On-Site Hydrogen Production Process Using Hybrid Data-Driven Model.
Jaewon Lee, Seokyoung Hong, Hyungtae Cho, Seongbin Ga, Junghwan Kim
(362y) Failure Stage Classification and Its Application to Predicting Remaining Useful Life of Bearings
Bahareh Hassani, Q. Peter He
(362j) Rnn and Transfer Learning for Battery Life Prediction of Electric Vehicles Based on Real-Road Driving Obd Data and Lab Measurements
Juri Lim, Dongil Shin, DongKuk Jang, Jaewook Lee
(362ac) Physics-Based Penalization for Hyperparameter Optimization in Gaussian Process Regression
Fani Boukouvala, Jinhyeun Kim, Kamran Paynabar, Christopher O. Luettgen
(362i) Virtual Sample Generation Based on Quantile Regression Variational Generative Adversarial Network for Soft-Sensing Modeling
Xiaohan Zhang, Qunxiong Zhu, Xunyuan Yin
(362h) Physics Informed Machine Learning for Feasibility Analysis
Zachary Kilwein, Michael Eydenberg, Logan Blakely, Fani Boukouvala
(362q) Multi-Rate Data-Driven Models for Lactic Acid Fermentation - Parameter Identification and Prediction
Satish Parulekar, Jingwei Gan
(362g) Soft Actor-Critic Deep Reinforcement Learning with Hybrid Actions for Scheduling of Energy Systems Under Demand Response
Gustavo Campos, Nael El-Farra, Ahmet Palazoglu
(362p) Data-Driven Modeling of Complex Nonlinear Systems Using Hybrid Series and Parallel Nonlinear Static – Dynamic Stochastic Neural Networks
Angan Mukherjee, Debangsu Bhattacharyya
(362f) Development of Bayesian Machine Learning Algorithms for Optimal Nonlinear Model Selection and Parameter Estimation from Noisy Data of Unknown Characteristics
Samuel Adeyemo, Debangsu Bhattacharyya
(362e) A Comparative Evaluation of Machine Learning Algorithms in Predicting Syngas Fermentation Outcomes Using Limited Experimental Data
Garrett Roell, Ni Wan, Ashik Sathish, Zhiyou Wen, Yinjie Tang, Forrest Sheng Bao
(362s) Developing Risk Assessment Framework for Wildfire in the United States – a Deep Learning Approach
Pingfan Hu, Qingsheng Wang, Zhuoran Zhang
(362w) Cover Cut Based Algorithm for Optimal Sensor Network Design
Nabil Magbool Jan, Arjun M
(362r) Modeling Dynamics of Material Flows in Coupled Industrial Processes Using Data Driven System Identification
William Farlessyost, Shweta Singh
(362v) Experimental Evaluation of the Level Detection in Separators Using Electrical Tomography
Antti Nissinen, Arto Voutilainen, Pekka Kaunisto, Jonathan Vänskä, Mika Tienhaara
(362aa) Process Monitoring and Online Fault Detection and Diagnosis Using Deep Recurrent Neural Networks on Plant Data
Lucky E. Yerimah, Sambit Ghosh, Yajun Wang, Yanan Cao, Jesus Flores-Cerrillo, B. Wayne Bequette
(362l) Cost Optimization of Steel Alloying Elements with Machine Learning Based Jominy Hardness Profile Prediction
Louis Allen, Peyman Z. Moghadam, Joan Cordiner
(362k) Accurate Surrogate Models for Stochastic Simulations Using Parin: Parameter As Input-Variable
Samira Mohammadi, Selen Cremaschi
(362ab) Digitalization of an Experimental Electrochemical Reactor Via the Smart Manufacturing Innovation Platform
Junwei Luo, Berkay Citmaci, Prakashan Korambath, Joonbaek Jang, Carlos Morales-Guio, Jim Davis, Panagiotis Christofides
(362u) High-Throughput Screening for Identifying Potential Chemical Exposure Scenarios at End-of-Life Stage
Jose Hernandez-Betancur, Gerardo Ruiz-Mercado, Mariano Martin
(362o) Improved Performance of Artificial Neural Networks Via Hyperparameter Optimization and Data Augmentation for a Small Number of Data Sets
Young-Il Lim, Pyeong-Gon Jung
(362n) Predicting Activity Coefficients at Infinite Dilution Using Hybrid Residual Graph Neural Networks
Edgar Ivan Sanchez Medina, Steffen Linke, Kai Sundmacher, Martin Stoll
(362z) Root Cause Identification Using Cross-Correlation Weighted Lag in Chemical Plants
Abhishek Bansal, Navadha Mankodi, Mohd Faheem Ullah, Resmi Suresh, Raghunathan Rengaswamy
(362m) Hybrid, Interpretable Machine Learning for Thermodynamic Property Estimation Using Grammar2vec for Molecular Representation
Vipul Mann, Karoline Brito, Rafiqul Gani, Venkat Venkatasubramanian