This is what predicts the fullness of each library at the specific times of the day.
- Junior Library
- Interface for server to get data
- Senior Library
- Testing output
- Place this with the server code and import the file "getData.py"
- addData.cpp requires an external json library which can be found here: https://github.com/nlohmann/json
- Download the single header useage of it, and place that into the appropriate directory.
| year | 2018 | 2019 | 2020 | 2021 |
| prediction | 23 | 18 | 43 | 36 |
| weight | 3 | 2 | 0 | 4 |
From this each prediction will be multiplied by its value and summed
23*4 + 18*2 +43*0 + 36*4 = 272
This result will be divided by the sum of all the weight values
3 + 2 + 4 = 9
272/9 = 30.22
Therefore the predicted value will be 30