SCEJ 87th Annual Meeting (Kobe, 2022)
Last modified: 2022-03-04 12:00:00
Program search result : 予測 : 14 programs
Program of CS-2 is updated.
The preprints are now open (Mar. 2nd). These can be viewed by clicking the Paper IDs. The ID/PW sent to the Registered participants in Period I/II and invited persons are required. (The participants registered in Period III will get the ID/PW on Mar. 15th.)
The yellow back on the Technical sessions page denotes streaming-live session. (HQ-21 is changed to online.)
The preprints are now open (Mar. 2nd). These can be viewed by clicking the Paper IDs. The ID/PW sent to the Registered participants in Period I/II and invited persons are required. (The participants registered in Period III will get the ID/PW on Mar. 15th.)
The yellow back on the Technical sessions page denotes streaming-live session. (HQ-21 is changed to online.)
Title (J) field includes “予測”; 14 programs are found.
The search results are sorted by the start time.
| Time | Paper ID | Title / Authors | Keywords | Topic code | Ack. number |
|---|---|---|---|---|---|
| Day 1 | H115 | [Divisional Award] TBD | Divisional Award | X-51 | 755 |
| Day 1 | PA148 | Sequence-based prediction of antibody properties by machine learning. | bioinformatics sequence | 7-f | 534 |
| Day 1 | H117 | [Divisional Award] Generalization of Condition for Unpredictable Dynamics of Polymeric Reacting Flow by Comparison between Pre- and Post-Reaction Fluid Properties | flow dynamics reacting flow Weissenberg effect | X-51 | 756 |
| Day 2 | PB263 | Re-identification of a FCC Process under Model Predictive Control Using Selective Excitation | Model predictive control Dual control Re-identification | 6-d | 41 |
| Day 2 | PB267 | Prediction of a feed factor for feeding premixed powder from a twin screw feeder | Twin screw feeder Feed factor Premixed powder | 6-g | 167 |
| Day 2 | PB236 | Prediction of degradation of 1,4-Dioxane using CSTR and stripping | 1,4-Dioxane Stripping CSTR | 4-c | 222 |
| Day 2 | PB238 | Prediction of adsorption amount of aromatic hydrocarbons in organoclay by machine learning | organoclay machine learning adsorption | 4-e | 441 |
| Day 2 | PB268 | Development of a quality prediction model using near infrared spectroscopy in table-top tablet production | Personalised medicine NIR PLS model | 6-f | 324 |
| Day 2 | H207 | [Requested talk] TBD | F-1 | 751 | |
| Day 2 | PC248 | Study of Machine Learning Using Irradiation Estimation Model and Measured Values for Predicting PV Power Generation Including Shadows | Energy system Solar cell Simulation | 9-e | 629 |
| Day 2 | B218 | Use of machine learning and feature engineering for product composition prediction in heavy oil catalytic cracking reactions | machine learning feature engineering catalytic cracking | CS-1 | 484 |
| Day 3 | M302 | Improvement of MPC Performance and Maintenance Scheme Utilizing Cyber Physical System for the Raw Mix Proportioning in Cement Industry | Model predictive control Cyber physical system Cement | 6-d | 56 |
| Day 3 | PD367 | Construction of product yield prediction model using machine learning in co-processing of bio-oil and heavy oil in fluid catalytic cracking | bio-oil co-processing machine learning | 5-a | 561 |
| Day 3 | I314 | Antiviral Catechin cocrystallization prediction by machine learning | cocrystallization machine learning catechin | 1-b | 442 |
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SCEJ 87th Annual Meeting (Kobe, 2022)
© 2023 The Society of Chemical Engineers, Japan. All rights reserved.For more information contact Organizing Committee of SCEJ 87th Annual Meeting (Kobe 2022) and IChES 2022
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