V2G Demand Prediction Based on Daily Pattern Clustering and Artificial Neural Networks-Reference-Cited by-同舟云学术

V2G Demand Prediction Based on Daily Pattern Clustering and Artificial Neural Networks

Published:2017 Issue: Volume: Page:113-119
ISSN:0302-9743
Container-title:Advances in Neural Networks - ISNN 2017
language:
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Author:

Lee Junghoon,Park Gyung-Leen

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-59072-1_14

Reference10 articles.

1. Ramchrun, S., Vytelingum, R., Rogers, A., Jennings, N.: Putting the ‘Smarts’ into the smart grid: a grand challenge for artificial intelligence. Commun. ACM 55(4), 89–97 (2012)

2. Bayram, I., Shakir, M., Abdallah, M., Qaraqe, K.: A survey on energy trading in smart grid. In: IEEE Global Conference on Signal and Information Processing, pp. 258–262 (2014)

3. Lee, J., Park, G.: A heuristic-based electricity trade coordination for microgrid-level V2G services. Int. J. Veh. Des. 69(1/2/3/4), 208–223 (2015)

4. Lee, J., Park, G., Cho, Y., Kim, S., Jung, J.: Spatio-temporal analysis of state-of-charge streams for electric vehicles. In: 4th ACM/IEEE International Conference on Information Processing in Sensor Networks, pp. 368–369 (2015)

5. Goiri, I., Le, K., Nguyen, T., Guitart, J., Torres, J., Bianchini, R.: GreenHadoop: leveraging green energy in data-processing frameworks. In: Proceedings of Eurosys (2012)

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