Zobrazeno 1 - 10
of 110
pro vyhledávání: '"Sjöblom, Jonas"'
In this paper, we propose machine learning solutions to predict the time of future trips and the possible distance the vehicle will travel. For this prediction task, we develop and investigate four methods. In the first method, we use long short-term
Externí odkaz:
http://arxiv.org/abs/2303.15087
Autor:
Ingers, Jacob, Sjöblom, Jonas
The connected car is rapidly becoming the norm in the automotive industry. With connected devices playing such a big part in today’s society our view of what constitutes a car is beginning to change. The new technologies that has become a part of t
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-320183
We present a three-way catalyst (TWC) cold-start model, calibrate the model based on experimental data from multiple operating points, and use the model to generate a Pareto-optimal cold-start controller suitable for implementation in standard engine
Externí odkaz:
http://arxiv.org/abs/2104.12390
Publikováno v:
Machine Learning, 111, 3839-3865, 2022
Trip destination prediction is an area of increasing importance in many applications such as trip planning, autonomous driving and electric vehicles. Even though this problem could be naturally addressed in an online learning paradigm where data is a
Externí odkaz:
http://arxiv.org/abs/2101.04520
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
In Applied Energy 1 November 2022 325
Publikováno v:
In Energy Policy August 2022 167
Publikováno v:
Industrial & Engineering Chemistry Research; 10/16/2024, Vol. 63 Issue 41, p17462-17476, 15p
Publikováno v:
In Fuel 1 November 2021 303
Publikováno v:
In Chemical Engineering Journal 1 August 2021 417