Improved Local Weather Forecasts Using Artificial Neural Networks

Morten Gill Wollsen; Bo Nørregaard Jørgensen

doi:10.1007/978-3-319-19638-1_9

Improved Local Weather Forecasts Using Artificial Neural Networks

Morten Gill Wollsen, Bo Nørregaard Jørgensen

Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review

Abstract

Solar irradiance and temperature forecasts are used in many different control systems. Such as intelligent climate control systems in commercial greenhouses, where the solar irradiance affects the use of supplemental lighting. This paper proposes a novel method to predict the forthcoming weather using an artificial neural network. The neural network used is a NARX network, which is known to model non-linear systems well. The predictions are compared to both a design reference year as well as commercial weather forecasts based upon numerical modelling. The results presented in this paper show that the network outperforms the commercial forecast for lower step aheads (< 5). For larger step aheads the network’s performance is in the range of the commercial forecast. However, the neural network approach is fast, fairly precise and allows for further expansion with higher resolution.

Originalsprog	Engelsk
Titel	Distributed Computing and Artificial Intelligence, 12th International Conference, DCAI 2015
Redaktører	Sigeru Omatu, Qutaibah M. Malluhi, Grzegorz Bocewicz, Sara Rodríguez González, Edgardo Bucciarelli, Gianfranco Giulioni, Farkhund Iqba
Forlag	Springer
Publikationsdato	3. jun. 2015
Sider	75-86
ISBN (Trykt)	978-3-319-19637-4
ISBN (Elektronisk)	9783319196374
DOI	https://doi.org/10.1007/978-3-319-19638-1_9
Status	Udgivet - 3. jun. 2015
Begivenhed	12th International Symposium on Distributed Computing and Artificial Intelligence - University of Salamanca, Spanien Varighed: 3. jun. 2015 → 5. jun. 2015 Konferencens nummer: DCAI

Konference

Konference	12th International Symposium on Distributed Computing and Artificial Intelligence
Nummer	DCAI
Lokation	University of Salamanca
Land/Område	Spanien
Periode	03/06/2015 → 05/06/2015

Navn	Advances in Intelligent Systems and Computing
Vol/bind	373
ISSN	2194-5357

Dokumenter og links

10.1007/978-3-319-19638-1_9

Citationsformater

Wollsen, M. G., & Jørgensen, B. N. (2015). Improved Local Weather Forecasts Using Artificial Neural Networks. I S. Omatu, Q. M. Malluhi, G. Bocewicz, S. R. González, E. Bucciarelli, G. Giulioni, & F. Iqba (red.), Distributed Computing and Artificial Intelligence, 12th International Conference, DCAI 2015 (s. 75-86). Springer. https://doi.org/10.1007/978-3-319-19638-1_9

Wollsen, Morten Gill ; Jørgensen, Bo Nørregaard. / Improved Local Weather Forecasts Using Artificial Neural Networks. Distributed Computing and Artificial Intelligence, 12th International Conference, DCAI 2015. red. / Sigeru Omatu ; Qutaibah M. Malluhi ; Grzegorz Bocewicz ; Sara Rodríguez González ; Edgardo Bucciarelli ; Gianfranco Giulioni ; Farkhund Iqba. Springer, 2015. s. 75-86 (Advances in Intelligent Systems and Computing, Bind 373).

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title = "Improved Local Weather Forecasts Using Artificial Neural Networks",

abstract = "Solar irradiance and temperature forecasts are used in many different control systems. Such as intelligent climate control systems in commercial greenhouses, where the solar irradiance affects the use of supplemental lighting. This paper proposes a novel method to predict the forthcoming weather using an artificial neural network. The neural network used is a NARX network, which is known to model non-linear systems well. The predictions are compared to both a design reference year as well as commercial weather forecasts based upon numerical modelling. The results presented in this paper show that the network outperforms the commercial forecast for lower step aheads (< 5). For larger step aheads the network{\textquoteright}s performance is in the range of the commercial forecast. However, the neural network approach is fast, fairly precise and allows for further expansion with higher resolution.",

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Wollsen, MG & Jørgensen, BN 2015, Improved Local Weather Forecasts Using Artificial Neural Networks. i S Omatu, QM Malluhi, G Bocewicz, SR González, E Bucciarelli, G Giulioni & F Iqba (red), Distributed Computing and Artificial Intelligence, 12th International Conference, DCAI 2015. Springer, Advances in Intelligent Systems and Computing, bind 373, s. 75-86, 12th International Symposium on Distributed Computing and Artificial Intelligence, Spanien, 03/06/2015. https://doi.org/10.1007/978-3-319-19638-1_9

Improved Local Weather Forecasts Using Artificial Neural Networks. / Wollsen, Morten Gill; Jørgensen, Bo Nørregaard.
Distributed Computing and Artificial Intelligence, 12th International Conference, DCAI 2015. red. / Sigeru Omatu; Qutaibah M. Malluhi; Grzegorz Bocewicz; Sara Rodríguez González; Edgardo Bucciarelli; Gianfranco Giulioni; Farkhund Iqba. Springer, 2015. s. 75-86 (Advances in Intelligent Systems and Computing, Bind 373).

Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review

TY - GEN

T1 - Improved Local Weather Forecasts Using Artificial Neural Networks

AU - Wollsen, Morten Gill

AU - Jørgensen, Bo Nørregaard

N1 - Conference code: DCAI

PY - 2015/6/3

Y1 - 2015/6/3

N2 - Solar irradiance and temperature forecasts are used in many different control systems. Such as intelligent climate control systems in commercial greenhouses, where the solar irradiance affects the use of supplemental lighting. This paper proposes a novel method to predict the forthcoming weather using an artificial neural network. The neural network used is a NARX network, which is known to model non-linear systems well. The predictions are compared to both a design reference year as well as commercial weather forecasts based upon numerical modelling. The results presented in this paper show that the network outperforms the commercial forecast for lower step aheads (< 5). For larger step aheads the network’s performance is in the range of the commercial forecast. However, the neural network approach is fast, fairly precise and allows for further expansion with higher resolution.

AB - Solar irradiance and temperature forecasts are used in many different control systems. Such as intelligent climate control systems in commercial greenhouses, where the solar irradiance affects the use of supplemental lighting. This paper proposes a novel method to predict the forthcoming weather using an artificial neural network. The neural network used is a NARX network, which is known to model non-linear systems well. The predictions are compared to both a design reference year as well as commercial weather forecasts based upon numerical modelling. The results presented in this paper show that the network outperforms the commercial forecast for lower step aheads (< 5). For larger step aheads the network’s performance is in the range of the commercial forecast. However, the neural network approach is fast, fairly precise and allows for further expansion with higher resolution.

U2 - 10.1007/978-3-319-19638-1_9

DO - 10.1007/978-3-319-19638-1_9

M3 - Article in proceedings

SN - 978-3-319-19637-4

T3 - Advances in Intelligent Systems and Computing

SP - 75

EP - 86

BT - Distributed Computing and Artificial Intelligence, 12th International Conference, DCAI 2015

A2 - Omatu, Sigeru

A2 - Malluhi, Qutaibah M.

A2 - Bocewicz, Grzegorz

A2 - González, Sara Rodríguez

A2 - Bucciarelli, Edgardo

A2 - Giulioni, Gianfranco

A2 - Iqba, Farkhund

PB - Springer

T2 - 12th International Symposium on Distributed Computing and Artificial Intelligence

Y2 - 3 June 2015 through 5 June 2015

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Wollsen MG, Jørgensen BN. Improved Local Weather Forecasts Using Artificial Neural Networks. I Omatu S, Malluhi QM, Bocewicz G, González SR, Bucciarelli E, Giulioni G, Iqba F, red., Distributed Computing and Artificial Intelligence, 12th International Conference, DCAI 2015. Springer. 2015. s. 75-86. (Advances in Intelligent Systems and Computing, Bind 373). doi: 10.1007/978-3-319-19638-1_9