• 15 Citations
20182020
If you made any changes in Pure these will be visible here soon.

Fingerprint Dive into the research topics where Bart Stappers is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Learning systems Engineering & Materials Science
Electricity Engineering & Materials Science
Decision making Engineering & Materials Science
Multilayer neural networks Engineering & Materials Science
Neural networks Engineering & Materials Science
Linear regression Engineering & Materials Science
Artificial intelligence Engineering & Materials Science
Support vector machines Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2018 2020

  • 15 Citations
  • 1 Conference contribution
  • 1 Article

A class-driven approach based on long short-term memory networks for electricity price scenario generation and reduction

Stappers, B., Paterakis, N. G., Kok, J. K. K. & Gibescu, M., 13 Jan 2020, (Accepted/In press) In : IEEE Transactions on Power Systems.

Research output: Contribution to journalArticleAcademicpeer-review

Electricity
Decision making
Neural networks
Uncertainty
Power markets
15 Citations (Scopus)
8 Downloads (Pure)

Deep learning versus traditional machine learning methods for aggregated energy demand prediction

Paterakis, N. G., Mocanu, E., Gibescu, M., Stappers, B. & van Alst, W., 16 Jan 2018, 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Proceedings. Piscataway: Institute of Electrical and Electronics Engineers, p. 1-6 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Learning systems
Multilayer neural networks
Linear regression
Artificial intelligence
Support vector machines