Maple Syrup Production Predictor

🎯 BRIEF

The goal of the project was to build a multivariate time series forecaster to predict the production quantity of Maple Syrup for 2021 considering different factors that affect its production—Daily Precipitation, Daily Soil Moisture, Daily Temperature, and Eight Day NDVI (Normalized Difference Vegetation Index). Different metrics were used to assess the causality and stationarity of different time series and to build the most suitable Vector Auto Regressive model.

 GitHub → 

🤝 CONTRIBUTION

• Built a robust multivariate Vector Autoregressive Model to predict Maple Syrup production, securing 5th place out of 100 participants.

• Employed different statistical methods for stationarity check, lag order estimation, and parameter analysis. 

• Optimized and validated the model utilizing multiple metrics—MAPE, ME, AE, RMSE, etc.—to get the best MAPE of 5.5%.