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Forecasting of Solar Power using Quantum GA - GNN
by
D.K. Chaturvedi
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 128 - Number 3 |
| Year of Publication: 2015 |
| Authors: D.K. Chaturvedi |
10.5120/ijca2015906478
|
D.K. Chaturvedi . Forecasting of Solar Power using Quantum GA - GNN. International Journal of Computer Applications. 128, 3 ( October 2015), 15-19. DOI=10.5120/ijca2015906478
@article{
10.5120/ijca2015906478,
author = {
D.K. Chaturvedi
},
title = { Forecasting of Solar Power using Quantum GA - GNN },
journal = {
International Journal of Computer Applications
},
issue_date = { October 2015 },
volume = { 128 },
number = { 3 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = {
15-19
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume128/number3/22852-2015906478/
},
doi = { 10.5120/ijca2015906478 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:20:17.154864+05:30
%A D.K. Chaturvedi
%T Forecasting of Solar Power using Quantum GA - GNN
%J International Journal of Computer Applications
%@ 0975-8887
%V 128
%N 3
%P 15-19
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Artificial Neural Network has been popularly used for forecasting purposes over the past. There are some innate problems in neural network such as indefinite configuration, architecture, and learning issues, etc. To vanquish these problems, Generalized Neural Network (GNN) has been used. This paper illustrates the development of Quantum GA-GNN method for forecasting of solar photovoltaic system power output. The actual data has been collected from the solar system installed at the rooftop of the University building and processed. The forecasting models also developed using Artificial Neural Network (ANN), and the results are compared.
References
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Index Terms
Computer Science
Information Sciences
Keywords