Institutsseminar/2021-04-09 Zusatztermin

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Version vom 14. Januar 2022, 13:17 Uhr von Erik Burger (Diskussion | Beiträge)
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Termin (Alle Termine)
Datum Freitag, 9. April 2021
Uhrzeit 11:30 – 12:00 Uhr (Dauer: 30 min)
Ort
Webkonferenz https://conf.dfn.de/webapp/conference/979148706
Vorheriger Termin Fr 26. März 2021
Nächster Termin Fr 9. April 2021

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Vorträge

Vortragende(r) Nico Denner
Titel Theory-Guided Data Science for Battery Voltage Prediction: A Systematic Guideline
Vortragstyp Bachelorarbeit
Betreuer(in) Pawel Bielski
Vortragsmodus
Kurzfassung Purely data-driven Data Science approaches tend to underperform when applied to scientific problems, especially when there is little data available. Theory-guided Data Science (TGDS) incorporates existing problem specific domain knowledge in order to increase the performance of Data Science models. It has already proved to be successful in scientific disciplines like climate science or material research.

Although there exist many TGDS methods, they are often not comparable with each other, because they were originally applied to different types of problems. Also, it is not clear how much domain knowledge they require. There currently exist no clear guidelines on how to choose the most suitable TGDS method when confronted with a concrete problem.

Our work is the first one to compare multiple TGDS methods on a time series prediction task. We establish a clear guideline by evaluating the performance and required domain knowledge of each method in the context of lithium-ion battery voltage prediction. As a result, our work could serve as a starting point on how to select the right TGDS method when confronted with a concrete problem.

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