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weather-conditions

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Machine Learning Project for classifying Weather into ThunderStorm (0001) , Rainy(0010) , Foggy (0100) , Sunny(1000) and also predict weather features for next one year after training on 20 years data on a neural network This is my first Machine Learning Project. Steps To run the project: Extract the files into a single directory ( say "MyWeatherProject" ) Open Octave(GUI) and go to the above directory Type the following in the COMMAND WINDOW : "YearlyForecast();" (without double quotes) Open the files "PredictionWeather1997.txt" to "PredictionWeather2016.txt" and compare with actual results from "Weather1997.txt" to "Weather2015.txt". Curves are plotted to compare predictions with actual weather conditions and they will be saved in the same directory...

  • Updated Nov 6, 2016
  • M
pd9mwo
pd9mwo commented Jan 17, 2022

look like there is an issue with the order to send to APRS-IS

PD9MWO-4>APRS,TCPIP*:@171407z5216.39N/00437.37E_110/004t049g012P000h83b10256L063Xaprs-weather-submit/1.4
but must be
PD9MWO-4>APRS,TCPIP*:@171407z5216.39N/00437.37E_110/004g012t049P000h83b10256L063Xaprs-weather-submit/1.4

the raw packets on aprs.fi
GOOD
2022-01-17 15:09:09 CET: PD9MWO-4>APRS,TCPIP*,qAC,T2EDM:@1714

bug good first issue

This demo reel, created as a final project for Advanced Graphics class, demonstrates several graphics techniques like Terrain Rendering, Level of Detail, Reflection, Global Illumination, Particle Effects. The scene shows a layout with mountains, hills, water bodies, natural vegetation, with effects of daytime and weather changes (rain/sunny) and involves a third person camera view.

  • Updated Nov 8, 2017

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