论文标题
使用机器学习使用模糊逻辑从卫星图像数据中识别风暴眼
Identification of storm eye from Satellite image data using fuzzy logic with machine learning
论文作者
论文摘要
这项研究介绍了一项针对识别风暴眼的独特技术的研究，该技术借助云图像，基于模糊逻辑和图像处理。模糊逻辑是一个术语，它是指由许多不同情况引起的不清楚行为的复杂系统。它提供了对风暴的动态行为进行建模的能力，并确定在感兴趣的领域中最佳眼睛的位置。之后，应用图像处理以根据搜索结果启用准确的眼睛定位。与印度气象部相比，实验结果是用大约$ 98 \％$准确地分析风暴眼位置，提供了最佳的田径数据，并提供了气象卫星研究的合作研究所，提供了进步Dvorak技术数据。结果，可以发现使用此技术对风暴的眼睛位置的识别可显着改善。使用目前的技术，可以完全自动确定眼睛，从而取代过去使用的手动方法。
This research presents a study of a unique technique for identifying storm eye that is based on fuzzy logic and image processing with the help of cloud images. Fuzzy logic is a term that refers to complicated systems with unclear behaviour caused by a number of different circumstances. It provides the ability to model the dynamic behavior of the storm and determines the location of the best eye in an area of interest. After that, image processing is applied to enable accurate eye positioning based on the search results. The experimental results are analyzing the storm eye position with approxiamtely $98\%$ accurate compared to the India meteorological department provided best track data and Cooperative Institute for Meteorological Satellite Studies provided Advances Dvorak Technique data. As a result, the identification of storm's eye location using this technique can be found to improve significantly. Using the present technique, it is possible to determine the eye entirely automatically, which replacing the manual method that has been employed in the past.
