Julian R. Camargo L. ¹, Ernesto Gomez Vargas ¹, Cesar A. Perdomo Ch. ¹

Affiliations
1 Department of Electronic Engineering , Engineering Faculty, Distrital Francisco Jose de Caldas University, Bogota D.C., CO

Abstract

Objectives: The aim of this work is show the analysis of the data measured by weather radar used in data mining and fuzzy logic. Methods/Analysis: A decoding of the data measured by the meteorological radar was made, which was encrypted, then an analysis of this data was made using neural networks that are trained with 10 and 20 neurons, in each case the effectiveness of each one is checked. Findings: The results showed that neural networks are an excellent tool that allows eliminate erroneous information and then normalize it to the scale used according to the standard. Improvements: This knowledge is essential for the aviation industry to operate properly and without risks for passengers, crew and aircraft, it is also important to anticipate and/or avoid, if possible, catastrophes generated by weather events related to rainfall.

Keywords

Data Mining, Neural Networks, Polarimetric Variables, Reflectivity, Weather Radar

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Mario A. Gomez N. ¹, Julian R. Camargo L. ², Cesar A. Perdomo Ch ²

Affiliations
1 Wavecomm Corporation, Bogota D.C., CO
2 Universidad Distrital Francisco Jose de Caldas, Bogota D.C, CO

Abstract

Objectives: Design and build an electronic audiovisual warning device for land transport vehicles operators which allows correcting, in real time, operation errors for overstep the speed limits and/or acceleration established. Additionally, the device allows the identification by keyboard of the vehicle operator for the subsequent generation of individualized statistics. Methods/Analysis: This investigation will allow the development of an electronic equipment that alerts the land vehicles operator, in real time and at the moment when they are getting out of control in some of the critical variables for safe driving, namely speed and acceleration, allowing to correct the mistakes, thanks to a timely and easy to understand information. Findings: The incorporation of electronic early warning devices of common driving errors for land transport operators allows a significant reduction in road accident rates, thanks to the stimulation of self-care and self-control, by means of agile and timely information within the vehicle cabin. Improvements: Currently the major research in this subject is around the training and investigation of accidents but do not have many objective tools to measure and qualify operators in the application of the standards and improvement plans that are taught (industrial safety, basic driving, traffic regulations, defensive driving and basic mechanics, among others).

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