Firstly, the GridSat data set and the satellite of China Meteorological Administration were used to analyze the tropical cyclone scale data, and the typhoon data set was established. Secondly, based on the Pytorch deep learning framework developed by Facebook, YOLO V5 is trained with the 1994鈥 ...
To do that, the position of a TC should be located and its intensity classified. In this chapter, we briefly introduce the problem of TC positioning and classification, discuss its associated data complexity issues, and suggest future research directions in the field.关键词: Book_Chapter ...
Köppen's climatic classification, characterized by a mean temperature of the coldest month of 64.4°F (18°C) or higher, and by a mean annual precipitation, in inches, greater than 0.44(t-a), where t is the mean annual temperature in degrees Fahrenheit, and a equals 32 for ...
Coastal flooding as a combined effect of storm-tides, river discharge (RD) and rainfall during a cyclone period is of a major concern, particularly, in the river delta regions. The low-lying Mahanadi river delta located in the maritime state of Odisha along the east coast of India is highl...
Classification of tropical cyclone rain patterns using convolutional autoencoderRAINFALLTROPICAL cyclonesVERTICAL wind shearSTORMSHeavy rainfall produced by tropical cyclones (TCs) frequently causes wide-spread damage. TCs have different patterns of rain depending on their development stage, geographical location...
WEATHER forecastingThe Statistical Hurricane Intensity Prediction Scheme (SHIPS) is a multiple linear regression model for predicting tropical cyclone (TC) intensity. It has been widely used in operational centers because of forecast stability, high accuracy, easy interpretation, and low com...
tropical cyclone intensityhierarchical PSO algorithmclassification and forecastingC45 AlgorithmBased on the tropical cyclone(TC) observations in the western North Pacific from 2000 to 2008, this paper adopts the particle swarm optimization(PSO) algorithm of evolutionary computation to optimize one comprehensiv...
machine learning classificationSouthwest Pacific Ocean basinTropical cyclone developmentThis study evaluates the ability of machine learning algorithms to classify tropical depressions (TDs) and tropical storms (TSs) in the western region of the southwest Pacific Ocean (SWPO). Decision rules are generated...
Based on the tropical cyclone(TC) observations in the western North Pacific from 2000 to 2008, this paper adopts the particle swarm optimization(PSO) algorithm of evolutionary computation to optimize one comprehensive classification rule, and apply the optimized classific...
Diagnosing Tropical Cyclone Rapid Intensification using Support Vector Machine ClassificationForecasting rapid intensification (RI) of tropical cyclones is a challenge due to limited understanding of the meteorological processes necessary to predict RI. Recent research identified large-scale synoptic controls ...