Joint Feature Selection and Parameter Tuning for Short-Term Traffic Flow Forecasting Based on Heuristically Optimized Multi-layer Neural Networks-Reference-Cited by-同舟云学术

Joint Feature Selection and Parameter Tuning for Short-Term Traffic Flow Forecasting Based on Heuristically Optimized Multi-layer Neural Networks

Published:2017 Issue: Volume: Page:91-100
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
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Author:

Laña Ibai,Del Ser Javier,Vélez Manuel,Oregi Izaskun

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-10-3728-3_10

Reference21 articles.

1. Van Hinsbergen, C.P., Van Lint, J.W., Sanders, F.M.: Short term traffic prediction models. In: Proceedings of the 14th World Congress on Intelligent Transport Systems (ITS), Beijing, pp. 22–41 (2007)

2. Vlahogianni, E.I., Karlaftis, M.G., Golias, J.C.: Short-term traffic forecasting: where we are and where we’re going. Transp. Res. Part C: Emerg. Technol. 43, 3–19 (2014)

3. Dunne, S., Ghosh, B.: Regime-based short-term multivariate traffic condition forecasting algorithm. J. Transp. Eng. 138(4), 455–466 (2011)

4. IFIP Advances in Information and Communication Technology;H Yang,2015

5. Lecture Notes in Computer Science;W Zhang,2015

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