Author: George Paw Date: 29/11/2017
This is a simple project to simulator weather into a specific output as listed below:
Sydney|-33.86,151.2,39|2017-11-29T01:19:25Z|Sunny|+0|-4.68668655|2
Melbourne|-37.73,144.91,78|2017-11-29T01:19:25Z|Sunny|+0|-9.3733731|53
Adelaide|-34.93,138.58,29|2017-11-29T01:19:25Z|Sunny|+0|-3.48497205|32
Location is an optional label describing one or more positions
Position is a comma-separated triple containing latitude, longitude, and elevation in metres above sea
level
Local time is an ISO8601 date time
Conditions is either Snow, Rain, Sunny
Temperature is in °C
Pressure is in hPa, and
Relative humidity is a %
- Install requirements.txt, recommend using virtual environment
- Navigate to \master\
- Execute in terminal "python GenerateWeather.py"
- Follow the command prompts
- The script will generate a fixed amount of station data in a datastream format as mentioned above
Optional: run nn.py to generate a new neural network fitting based on CSV file
Theory: Output all stations at the same time, data per second is dependent on user.
The time is set to current time and every new datastream is at an hour interval into the future
This is a unsolicated output stream
Used Neural Network to predict temperature, the topology is as below:
Features: Latitude, Longtitude, Elevation, Temperature
Output: Temperature
Layer: 1000
Data obtained from https://data.gov.au/dataset/rainfall-and-temperature-forecast-and-observations-hourly-verification-2016-05-to-2017-04/resource/5920f661-79cc-4740-8d76-20cd11f033d4
- Stations are narrowed to 10 cities
- Custom values are not working yet
- Timezones are not taking into account
- Pressure only take into account elevation
- Humidity is currently a pseudo-random number generator
- Weather condition is a pseudo-random number generator
- Use more stations datapoints
- Fix custom values
- Enable solicated output stream
- Take timezones into consideration
- Allow python script to take arguments
- Construct better test scripts using pytest
- Find a better way to generate pressure (e.g. lookup table)
- Use rainfall temperature to calculate humidity
- Use time as a factor in neural network training
- Use neural network training to produce a better weather conditon prediciton
- Train neural network better