Modeling the energy consumption of trains by applying neural networks
[EN] This paper presents the training of a neural network using consumption data measured in the underground network of Valencia (Spain), with the objective of estimating the energy consumption of the systems. After the calibration and validation of the neural network using part of the gathered cons...
| Autores: | , , |
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| Tipo de documento: | artigo |
| Data de publicação: | 2018 |
| País: | España |
| Recursos: | Universitat Politècnica de València (UPV) |
| Repositório: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglês |
| OAI Identifier: | oai:riunet.upv.es:10251/132461 |
| Acesso em linha: | https://riunet.upv.es/handle/10251/132461 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Gradient Energy consumption Artificial neural networks Metro, Railway Track layout INGENIERIA E INFRAESTRUCTURA DE LOS TRANSPORTES |
| Resumo: | [EN] This paper presents the training of a neural network using consumption data measured in the underground network of Valencia (Spain), with the objective of estimating the energy consumption of the systems. After the calibration and validation of the neural network using part of the gathered consumption data, the results obtained show that the neural network is capable of predicting power consumption with high accuracy. Once fully trained, the network can be used to study the energy consumption of a metro system and for testing the hypothetical operation scenarios. |
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