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- Title
Prediction System of Cloud Distribution Image Using Fully Convolutional Networks.
- Authors
Koki Akiyama; Hiroshi Suzuki; Takahiro Kitajima; Takashi Yasuno
- Abstract
In this paper, we propose a cloud distribution prediction model in which fully convolutional networks are used to improve the prediction accuracy for photovoltaic power generation systems. The model learns the cloud distribution from meteorological satellite images and predicts the cloud image 60 min later. We examined the applicability of Day Microphysics RGB as input to the cloud image prediction model. Day Microphysics RGB is a type of RGB composite image based on the observation image of Himawari-8. It is used for daytime cloud analysis and can perform detailed cloud analysis, for example, the discrimination of cloud areas such as upper and lower clouds. The performance of the proposed method is evaluated on the basis of the root mean square error of the prediction and ground truth images.
- Subjects
IMAGE processing; CLOUD computing; CONVOLUTIONAL neural networks; PREDICTION models; REMOTE-sensing images
- Publication
Journal of Signal Processing (1342-6230), 2022, Vol 26, Issue 4, p127
- ISSN
1342-6230
- Publication type
Article
- DOI
10.2299/jsp.26.127