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Neural models predicting traction power consumption: support of e-energy telematic systems

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EATIS '09: Proceedings of the 2009 Euro American Conference on Telematics and Information Systems: New Opportunities to increase Digital Citizenship

Article No.: 22, Pages 1 - 4

https://doi.org/10.1145/1551722.1551744

Published: 03 June 2009 Publication History

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Abstract

This paper deals with determination of relevant input data for models predicting electric traction power consumption. Furthermore, it deals with developing such models, which combine knowledge of classical physics with methods of artificial neural networks. It is possible to design control processes of railway traction effectively, based on these models. Real data of electric power consumption of traction substations in the Czech Republic within one year of train diagram 2006/2007 validity are used for verification of the models. These models can build support for e-energy telematic systems.

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Cited By

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Haghbin MKhsoravani MGolzar Tehrani AFarjah E(2022)Applying a hybrid model considering the interaction between train and power system for energy consumption surveysIET Intelligent Transport Systems10.1049/itr2.1229217:7(1482-1491)Online publication date: 17-Oct-2022
https://doi.org/10.1049/itr2.12292
Martínez Fernández PSalvador Zuriaga PVillalba Sanchís IInsa Franco R(2019)Neural networks for modelling the energy consumption of metro trainsProceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit10.1177/0954409719861595234:7(722-733)Online publication date: 16-Jul-2019
https://doi.org/10.1177/0954409719861595

Index Terms

Neural models predicting traction power consumption: support of e-energy telematic systems
1. Mathematics of computing
  1. Probability and statistics
    1. Statistical paradigms
      1. Time series analysis

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Published In

EATIS '09: Proceedings of the 2009 Euro American Conference on Telematics and Information Systems: New Opportunities to increase Digital Citizenship

June 2009

207 pages

ISBN:9781605583983

DOI:10.1145/1551722

Conference Chair:
Miroslav Svitek,
Program Chair:
Tomas Zelinka

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 03 June 2009

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EATIS '09

EATIS '09: Euro American Conference on Telematics and Information Systems

June 3 - 5, 2009

Prague, Czech Republic

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Overall Acceptance Rate 17 of 64 submissions, 27%

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Haghbin MKhsoravani MGolzar Tehrani AFarjah E(2022)Applying a hybrid model considering the interaction between train and power system for energy consumption surveysIET Intelligent Transport Systems10.1049/itr2.1229217:7(1482-1491)Online publication date: 17-Oct-2022
https://doi.org/10.1049/itr2.12292
Martínez Fernández PSalvador Zuriaga PVillalba Sanchís IInsa Franco R(2019)Neural networks for modelling the energy consumption of metro trainsProceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit10.1177/0954409719861595234:7(722-733)Online publication date: 16-Jul-2019
https://doi.org/10.1177/0954409719861595

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Predicting power consumption of GPUs with fuzzy wavelet neural networks

Some Key Problems on Cophase Traction Power Supply Device

Performance comparison of artificial neural network models for daily rainfall prediction

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