With the spirit of reproducible research, this repository contains all the codes required to produce the results in the manuscript:
H. Wang, M. S. Pathan, Y. H. Lee, and S. Dev, Day-ahead Forecasts of Air Temperature, under review.
Climate change is a phenomenon that can affect many departments including health, development, and planning. In this reseach, we perform forecasting of ground-based air temperature. We evaluate the performance of our approach by computing the RMSE values.
All codes are written in python3.
forecasting-example1.py: Computes the forecasting performance and plots the result for sample example 1.forecasting-example2.py: Computes the forecasting performance and plots the result for sample example 2.benchmarking.py: Computes the performance of our proposed method, along with other benchmarking methods.
The results are stored in the folder ./results/.
prediction-index146.PDF: Plot of forecasting example 1.prediction-index20.PDF: Plot of forecasting example 2.comparison.txt: Text file that details the performance of the various benchmarking methods.
The dataset used in our case study can be found in the folder ./data/.