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SCEJ 52nd Autumn Meeting (Okayama, 2021)
Program search result : 予測 : 12 programs
ST-25,SY-56,SY-64,SY-65,SY-70 are changed from live streaming sessions to online sessions.
The preprints are now open (Sep. 8). These can be viewed by clicking the Paper IDs. The ID/PW sent to the Registered participants (excludes free registration) and invited persons are required.
The preprints are now open (Sep. 8). These can be viewed by clicking the Paper IDs. The ID/PW sent to the Registered participants (excludes free registration) and invited persons are required.
Title (J) field includes “予測”; 12 programs are found. (“Poster with Flash” presentations are double-counted.)
The search results are sorted by the start time.
| Time | Paper ID | Title / Authors | Keywords | Topic code | Ack. number |
|---|---|---|---|---|---|
| Day 1 | PA104 | Application of machine learning to prediction and improvement of target product yields in catalytic cracking of triglyceride | catalytic cracking triglyceride machine learning | SY-62 | 778 |
| Day 1 | VF106 | Prediction of carbon dioxide solubility in absorbents based on molecular information | carbon capture solubility quantum chemistry | SY-51 | 430 |
| Day 1 | VD107 | Analysis of PV power generation model considering shadow effect by multiple regression of actual data and operation-principle-based model | Energy system Solar cell Simulation | ST-23 | 837 |
| Day 1 | VG107 | 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 | SY-52 | 243 |
| Day 1 | VD108 | Comparison of Gaussian Process Regression with Linear Regression in Electricity Demand Forecasting Using Energy Data | distributed generation renewable energy machine learning | ST-23 | 639 |
| Day 1 | VF108 | Prediction of the Critical Parameters and Acentric Factor from a Generalized Vapor Pressure Correlation | vapor pressure critical point acentric factor | SY-51 | 291 |
| Day 1 | PA104 | Application of machine learning to prediction and improvement of target product yields in catalytic cracking of triglyceride | catalytic cracking triglyceride machine learning | SY-62 | 778 |
| Day 1 | LA123 | [Requested talk] Nano material data-bases and the prediction of materials properties | Nano Material Machine Learning Database | SP-2 | 103 |
| Day 2 | VT204 | Performance prediction of CO2 capture simulating change in thermodynamic properties of degraded amine solution | Process simulation Plant operation Heat capacity | SY-82 | 338 |
| Day 2 | PB231 | Prediction of Cofactor specificity of malic enzyme using machine learning | Enzyme Machine learning Cofactor | SY-67 | 429 |
| Day 2 | PB231 | Prediction of Cofactor specificity of malic enzyme using machine learning | Enzyme Machine learning Cofactor | SY-67 | 429 |
| Day 3 | VG302 | Thermal behavior by dimensionless numbers for mixing and microwave local heating | Microwave mixing Reynolds number temperature distribution | SY-55 | 153 |
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SCEJ 52nd Autumn Meeting (Okayama, 2021)
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