Using AWPSO to solve the data scarcity problem in wind speed prediction by artificial neural networks

Mohsen Fesharaki; Niusha Shafiabady; Mohsen A. Fesharaki; Shahab Ahmadi

doi:10.1109/AICI.2010.251

Using AWPSO to solve the data scarcity problem in wind speed prediction by artificial neural networks

Mohsen Fesharaki, Niusha Shafiabady, Mohsen A. Fesharaki, Shahab Ahmadi

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper published in Proceedings › peer-review

Abstract

A new strategy in wind speed prediction based on adaptive weighted particle swarm optimization combined with artificial neural networks was proposed. Regarding the data gathering, sometimes it is difficult to provide the neural network with sufficient data to be trained efficiently. In order to solve this problem Adaptive weighed particle swarm optimization is used to increase the data the produced data is fed to a multilayered feed forward neural network to predict the future wind speed. This method has lead to good estimated wind speed accuracy and good prediction performance.

Original language	English
Title of host publication	Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010
Pages	49-52
Number of pages	4
Volume	3
DOIs	https://doi.org/10.1109/AICI.2010.251
Publication status	Published - 2010
Externally published	Yes
Event	2010 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010 - Sanya, China Duration: 23 Oct 2010 → 24 Oct 2010

Publication series

Name	Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010
Volume	3

Conference

Conference	2010 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010
Country/Territory	China
City	Sanya
Period	23/10/10 → 24/10/10

Access to Document

10.1109/AICI.2010.251

Cite this

Fesharaki, M., Shafiabady, N., Fesharaki, M. A., & Ahmadi, S. (2010). Using AWPSO to solve the data scarcity problem in wind speed prediction by artificial neural networks. In Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010 (Vol. 3, pp. 49-52). [5655134] (Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010; Vol. 3). https://doi.org/10.1109/AICI.2010.251

Fesharaki, Mohsen ; Shafiabady, Niusha ; Fesharaki, Mohsen A. et al. / Using AWPSO to solve the data scarcity problem in wind speed prediction by artificial neural networks. Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010. Vol. 3 2010. pp. 49-52 (Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010).

@inproceedings{2c56100f24834c608d52e87977455c65,

title = "Using AWPSO to solve the data scarcity problem in wind speed prediction by artificial neural networks",

abstract = "A new strategy in wind speed prediction based on adaptive weighted particle swarm optimization combined with artificial neural networks was proposed. Regarding the data gathering, sometimes it is difficult to provide the neural network with sufficient data to be trained efficiently. In order to solve this problem Adaptive weighed particle swarm optimization is used to increase the data the produced data is fed to a multilayered feed forward neural network to predict the future wind speed. This method has lead to good estimated wind speed accuracy and good prediction performance.",

keywords = "Adaptive weighted particle swarm optimization, Data scarcity, Multilayered feed forward neural network, Predictio, Wind speed",

author = "Mohsen Fesharaki and Niusha Shafiabady and Fesharaki, {Mohsen A.} and Shahab Ahmadi",

year = "2010",

doi = "10.1109/AICI.2010.251",

language = "English",

isbn = "9780769542256",

volume = "3",

series = "Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010",

pages = "49--52",

booktitle = "Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010",

note = "2010 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010 ; Conference date: 23-10-2010 Through 24-10-2010",

}

Fesharaki, M, Shafiabady, N, Fesharaki, MA & Ahmadi, S 2010, Using AWPSO to solve the data scarcity problem in wind speed prediction by artificial neural networks. in Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010. vol. 3, 5655134, Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010, vol. 3, pp. 49-52, 2010 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010, Sanya, China, 23/10/10. https://doi.org/10.1109/AICI.2010.251

Using AWPSO to solve the data scarcity problem in wind speed prediction by artificial neural networks. / Fesharaki, Mohsen; Shafiabady, Niusha; Fesharaki, Mohsen A. et al.
Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010. Vol. 3 2010. p. 49-52 5655134 (Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010; Vol. 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper published in Proceedings › peer-review

TY - GEN

T1 - Using AWPSO to solve the data scarcity problem in wind speed prediction by artificial neural networks

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AU - Fesharaki, Mohsen A.

AU - Ahmadi, Shahab

PY - 2010

Y1 - 2010

N2 - A new strategy in wind speed prediction based on adaptive weighted particle swarm optimization combined with artificial neural networks was proposed. Regarding the data gathering, sometimes it is difficult to provide the neural network with sufficient data to be trained efficiently. In order to solve this problem Adaptive weighed particle swarm optimization is used to increase the data the produced data is fed to a multilayered feed forward neural network to predict the future wind speed. This method has lead to good estimated wind speed accuracy and good prediction performance.

AB - A new strategy in wind speed prediction based on adaptive weighted particle swarm optimization combined with artificial neural networks was proposed. Regarding the data gathering, sometimes it is difficult to provide the neural network with sufficient data to be trained efficiently. In order to solve this problem Adaptive weighed particle swarm optimization is used to increase the data the produced data is fed to a multilayered feed forward neural network to predict the future wind speed. This method has lead to good estimated wind speed accuracy and good prediction performance.

KW - Adaptive weighted particle swarm optimization

KW - Data scarcity

KW - Multilayered feed forward neural network

KW - Predictio

KW - Wind speed

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U2 - 10.1109/AICI.2010.251

DO - 10.1109/AICI.2010.251

M3 - Conference Paper published in Proceedings

SN - 9780769542256

VL - 3

T3 - Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010

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BT - Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010

T2 - 2010 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010

Y2 - 23 October 2010 through 24 October 2010

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Fesharaki M, Shafiabady N, Fesharaki MA, Ahmadi S. Using AWPSO to solve the data scarcity problem in wind speed prediction by artificial neural networks. In Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010. Vol. 3. 2010. p. 49-52. 5655134. (Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010). doi: 10.1109/AICI.2010.251

Using AWPSO to solve the data scarcity problem in wind speed prediction by artificial neural networks

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