## 1 Introduction  
A fast-rotating tropical cyclone storm circulating around a defined center is called a hurricane, and the severity of the occurrence of the hurricane depends on the location and strength of the storm. The cyclic wind movement induces a low pressure in the middle of the hurricane, and thus the air is pushed upwards and the wind flows through the center of the storm. As the wind speed increases, it becomes a tropical storm and emerges into a hurricane, which mostly occurs in the Atlantic Ocean and North Eastern Pacific Ocean with cyclic wind movement whose closed wind speed exceeds 75 mph [1]. Hurricanestend to grow when they take energy from the warm ocean water. When the wind speed increases, hurricanes strike the land, which incurs severe damage. Hurricanes can be categorized into various types depending on the wind speed parameter. Hurricanes with a wind speed of 74 mph or above are termed category 5 hurricanes, which are cataclysmic in nature [2]. When the wind speed exceeds the above threshold, it is impossible to prevent the occurrence of extreme weather event. A storm induces the abnormal rise of water called a storm surge, and the height of the water level can rise 20 feet or more above the sea level. This is called catastrophic, and the storm surge exceeds 19+ feet. The rise in the sea level that occurs during a tropical cyclone is called a storm surge, which generates strong winds that push the water into the shore and leads to flooding. Flooding and storm surges are the sequential disaster events triggered by hurricanes. The coastal regions are primarily affected by the storm surges, which cause colossal damage. Therefore, it is essential for the scientists to predict the formation of hurricanes using best prediction models well in advance to prevent damage and save human lives [3]. Table 1 shows the classifications of hurricanes with the sustained wind range values. In the stages of hurricane development, the formation of closed isobaric circulation is called tropical depression. Tropical depressions develop into tropical storms when the sustained wind velocity exceeds 63 km/h (39 mph) and is considered a threat. It turns into a hurricane when the wind speed exceeds 119 km/h and is considered as the destructive stage of the tropical storm. The characteristics of wind attributes over various measurement conditions should be analyzed for effective estimation of tropical cyclone intensity. Meteorologists face difficulties in predicting weather events using computational models because of the complexity and randomness involved in the weather variables. Various factors such as the volume of data availability and computational time to analyze and execute mainly depend on the complexity involved in the variables. The sources of data are combined from the observations of weather stations, satellites, and weather balloons. Satellite images such as cloud cover and water vapor changes in the atmosphere are used by scientists for accurate prediction. Numerical weather prediction (NWP) models are dependent on the existing weather models such as the movable fine mesh (MFM) model for tracking the hurricane, and the joint physics-based on machine learning (ML) models can achieve good performance when the output of the physics-based model is fed into the neural networks [4]. The major limitation of the NWP models is that if the forecast period increases, interpolation of a large volume of data occurs and takes more computational time for processing. In order to predict the changes in the atmospheric processes, mathematical models such as global circulation models are used for analysis. It is very difficult for the meteorologists to predict the localized precipitation and the thunderstorms present in the convective storms. If a higher number of processes are involved, the model may take more time to forecast, and there is always a trade-off between the computational speed, accuracy, and the complexity of parameters.