Výsledky vyhledávání - "Matthias Wastian"

Simulation And Optimization Of Traction Unit Circulations

Autor: Sarah Frisch, Matthias Wastian, Dominic Weinberger, Matthias Rößler, Niki Popper, Martin Bicher, Anna Jellen, Philipp Hungerländer

Publikováno v: WSC

The planning of traction unit circulations in a railway network is a very time-consuming task. In order to support the planning personnel, the paper proposes a combination of optimization, simulation and machine learning. This ensemble creates mathem

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c4214bd9410201c820183a58731e3d3f
https://doi.org/10.1109/wsc48552.2020.9383926

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From Machine Learning to Knowledge-Based Decision Support—A Predictive-Model-Markup-Language-to-Arden-Syntax Transformer for Decision Trees

Autor: Sergei B. Arseniev, Andrea Rappelsberger, Matthias Wastian, Julia Zeckl, Klaus-Peter Adlassnig, Dominik Brunmeir

Publikováno v: Studies in Computational Intelligence ISBN: 9783030495350

Arden Syntax is an HL7 International standard for the representation and execution of clinical knowledge in knowledge-based clinical decision support (CDS) systems. The predictive model markup language (PMML) specifies a file format for the represent

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c2fb8330d85f41c851aa88661e8d286f
https://doi.org/10.1007/978-3-030-49536-7_9

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Active consumer participation in smart energy systems

Autor: Andreas Fleischhacker, Lisa V. Eckerstorfer, Katja Corcoran, Barbara Glock, Gerald Schweiger, Matthias Rößler, Johannes Radl, Irene Hafner, Niki Popper, Matthias Wastian, Georg Lettner

Publikováno v: Energy and Buildings. 227:110359

A pressing task for future energy systems is the design and operation of systems that integrate large shares of renewable energy while improving overall system efficiency. Because buildings consume about 32% of the total global final energy use, they

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7a10982d3cd9ab8485f34d01dfd6fef3
https://doi.org/10.1016/j.enbuild.2020.110359

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More than Bags of Words: Sentiment Analysis with Word Embeddings

Autor: Elena Rudkowsky, Michael Sedlmair, Marcelo Jenny, Martin Haselmayer, Stefan Emrich, Matthias Wastian

Moving beyond the dominant bag-of-words approach to sentiment analysis we introduce an alternative procedure based on distributed word embeddings. The strength of word embeddings is the ability to capture similarities in word meaning. We use word emb

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::df78039b244968fd41db8be3af41caaf
https://hdl.handle.net/11353/10.937153

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