研究目的
The aim of this work is show the analysis of the data measured by weather radar used in data mining and fuzzy logic.
研究成果
Neural networks are an excellent tool for analyzing meteorological radar data, allowing for the elimination of erroneous information and normalization of data. This is essential for the aviation industry to operate safely and to anticipate weather-related catastrophes.
研究不足
The main difficulty in radar measurements is related to the diameter of the drops, which affects the accuracy of polarimetric variables like KDP and ZDR.
1：Experimental Design and Method Selection:
The study involves decoding encrypted data from meteorological radars and analyzing it using neural networks trained with 10 and 20 neurons.
2：Sample Selection and Data Sources:
Data generated by weather radar, specifically for the variable ZDR.
3：List of Experimental Equipment and Materials:
RadX software for decoding radar data, MATLAB for neural network simulation.
4：Experimental Procedures and Operational Workflow:
Decoding and transforming radar data into an appropriate format, cleaning erroneous information, normalizing data, and training neural networks.
5：Data Analysis Methods:
Neural network analysis to validate the possibility of rain in a specific area of the radar.
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