Javascript must be enabled to continue!
An Efficient Tropical Cyclone Center Prediction Scheme Using Firefly Algorithm in Infrared Image (IR)
View through CrossRef
Tropical cyclones have a strong potential to bring significant economic loss to cyclone-prone areas. Locating the tropical cyclone center is significant and necessary for the timely forecasting of tropical cyclones. The observation of the typhoon's center, primarily carried out through the use of infrared (IR) images, is not easy. In some situations, the typhoon center is identified by the typhoon eye, which is overlaid on an infrared image. Therefore, the purpose of this study is to address the challenges of tropical cyclone center localization in infrared images by developing a firefly algorithm-based optimization scheme for accurate center prediction. This research proposes an efficient tropical cyclone center prediction scheme with optimization performed by the firefly algorithm to predict the central point in tropical cyclone infrared images. In addition, problems associated with pattern matching and other localization challenges are addressed through the optimization process to obtain the most accurate tropical cyclone center. Finally, the proposed scheme achieved highly accurate center localization. The proposed approach contributes to the scientific community by providing an optimization-based framework for tropical cyclone center localization that can support future research in automated cyclone analysis, infrared satellite image processing, and the development of more reliable tropical cyclone forecasting methods.
Science Publishing Group
Title: An Efficient Tropical Cyclone Center Prediction Scheme Using Firefly Algorithm in Infrared Image (IR)
Description:
Tropical cyclones have a strong potential to bring significant economic loss to cyclone-prone areas.
Locating the tropical cyclone center is significant and necessary for the timely forecasting of tropical cyclones.
The observation of the typhoon's center, primarily carried out through the use of infrared (IR) images, is not easy.
In some situations, the typhoon center is identified by the typhoon eye, which is overlaid on an infrared image.
Therefore, the purpose of this study is to address the challenges of tropical cyclone center localization in infrared images by developing a firefly algorithm-based optimization scheme for accurate center prediction.
This research proposes an efficient tropical cyclone center prediction scheme with optimization performed by the firefly algorithm to predict the central point in tropical cyclone infrared images.
In addition, problems associated with pattern matching and other localization challenges are addressed through the optimization process to obtain the most accurate tropical cyclone center.
Finally, the proposed scheme achieved highly accurate center localization.
The proposed approach contributes to the scientific community by providing an optimization-based framework for tropical cyclone center localization that can support future research in automated cyclone analysis, infrared satellite image processing, and the development of more reliable tropical cyclone forecasting methods.
Related Results
A Machine Learning-Based Tropical Cyclone Precipitation Simulation in China
A Machine Learning-Based Tropical Cyclone Precipitation Simulation in China
Heavy precipitation is a major hazard associated with tropical cyclones, often causing substantial economic losses and casualties through secondary disasters such as floods, landsl...
Analisis Penggunaan Variasi Turbo Cyclone Terhadap Performa Kendaraan
Analisis Penggunaan Variasi Turbo Cyclone Terhadap Performa Kendaraan
Penelitian ini dilatar belakangi banyaknya kendaraan dengan usia pakai dan pola perawatan yang tidak rutin yang berakibat turunannya performa dan emisi yang meningkat. Penelitian i...
GIS Mapping for Distribution of Firefly along Sungai Sepetang, Perak
GIS Mapping for Distribution of Firefly along Sungai Sepetang, Perak
Kuala Sepetang is well known for its nocturnal firefly-watching activities, which contribute to ecotourism and can provide economic incentives for mangrove conservation. This study...
The Influence Of Atmosphere On Tropical Cyclone Freddy In The Lesser Sunda Islands
The Influence Of Atmosphere On Tropical Cyclone Freddy In The Lesser Sunda Islands
Indonesia frequently experiences atmospheric phenomena form Tropical Cyclone annually due to its geographical location situated in tropical regions. The occurrence of Tropical Cycl...
Simulating Changes in Tropical Cyclone Activity During the Deglaciation
Simulating Changes in Tropical Cyclone Activity During the Deglaciation
How tropical cyclones respond to climate change remains an open question. Due to recent increases in computing power and climate model resolution, it is now possible to explicitly ...
Synoptic analysis of Cyclone Ianos via surface, satellite and reanalysis data
Synoptic analysis of Cyclone Ianos via surface, satellite and reanalysis data
<p>Mediterranean Tropical-like Cyclones, or commonly named as medicanes are a special type of cyclone over the Mediterranean Sea. These cyclones are quite similar to ...
PREDICTION OF CYCLONE USING KALMAN SPATIO TEMPORAL AND TWO DIMENSIONAL DEEP LEARNING MODEL
PREDICTION OF CYCLONE USING KALMAN SPATIO TEMPORAL AND TWO DIMENSIONAL DEEP LEARNING MODEL
Cyclone Classification and Prediction models rely on large intensity based on the maximum speed of the wind, along with the classification of intensity. The computational constrain...
Antecedents for the Shapiro–Keyser Cyclone Model in the Bergen School Literature
Antecedents for the Shapiro–Keyser Cyclone Model in the Bergen School Literature
AbstractTwo widely accepted conceptual models of extratropical cyclone structure and evolution exist: the Norwegian and Shapiro–Keyser cyclone models. The Norwegian cyclone model w...

