An Assessment of Rainfall Forecast using Image Similarity Processing

Deeprasertkul, Prattana

doi:10.1145/3383812.3383821

Cited by 2 publications

(3 citation statements)

References 5 publications

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“…The image hashing codes are used to compare the images which are easier and faster method than using the whole of original images [18]. Figure 10: The process flow of the accurate measurement of rainfall forecasting model [5].…”

Section: Resultsmentioning

confidence: 99%

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A Monthly Rainfall Forecasting from Sea Surface Temperature Spatial Pattern

Deeprasertkul¹,

Chitradon²

2021

Adv. sci. technol. eng. syst. j.

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The ocean surface temperatures or sea surface temperatures have a significant influence on local and global weather. The change in sea surface temperatures will lead to the change in rainfall patterns. In this paper, the long-term rainfall forecasting is developed for planning and decision making in water resource management. The similarity of sea surface temperature images pattern that was applied to analyze and develop the monthly rainfall forecasting model will be proposed. In this work, the convolutional neural network and autoencoder techniques are applied to retrieve the similar sea surface temperature images in database store. The accuracy values of the monthly rainfall forecasting model which is the long-term forecasting were evaluated as well. The average value of the model accuracies was around 82.514%.

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Section: Resultsmentioning

confidence: 99%

“…This model has predicted the monthly rainfall amount in image format. This is the improvement of the data-driven analytics which is a project of Hydro -Informatics Institute (Public Organization) [5].…”

Section: Introductionmentioning

confidence: 99%

A Monthly Rainfall Forecasting from Sea Surface Temperature Spatial Pattern

Deeprasertkul¹,

Chitradon²

2021

Adv. sci. technol. eng. syst. j.

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“…The improvement of image similarity evaluation of the rainfall forecasting model should be measured for representing the system efficiency as well. In the previous work [7], we assessed the model with a perceptual hash technique which generated the hash strings by the hash algorithm. A perceptual hash function calculates similar perceptual hash strings for similar images by comparing and measuring two perceptual hashes.…”

Section: Imentioning

confidence: 99%

An Image Similarity Evaluation in Rainfall Forecasting Model

Deeprasertkul¹

2020

IJCIT

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The Global Satellite Mapping of Precipitation or GSMaP data which is used to display the rainfall data was used to analyze and create the rainfall forecasting model. This work is the evaluation of this rainfall forecasting model which is the short-term forecast. The GSMaP forecasting data were matched with the GSMaP history data and calculate their similarity values by applying the original image matching method. The modification of Rainfall Forecasting Model and its evaluation that applied the original image instead of the image hash improve the accuracy of rainfall forecasted results.

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An Assessment of Rainfall Forecast using Image Similarity Processing

Cited by 2 publications

References 5 publications

A Monthly Rainfall Forecasting from Sea Surface Temperature Spatial Pattern

A Monthly Rainfall Forecasting from Sea Surface Temperature Spatial Pattern

An Image Similarity Evaluation in Rainfall Forecasting Model

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