Forecasting Sales for the Next Two Years

Overview of My Submission

We developed a great forecasting application. When you enter the monthly sales data of your products in the past two years, our application reports how much your product will be sold for each month of the next two years with 4 different forecasting methods. These forecasting methods are "Exponential Smoothing","Double Exponential Smoothing","Regression Analysis" and "Deseasonalized Regression Analysis". MSE is calculated for each method and the method with the lowest error rate is determined. But you can get the reports of all other forecasting methods.

Submission Category:

Choose Your Own Adventure

Link to Code

Forecast Sales for the Next Two Years

1. Introduction

When you enter the monthly sales data of your products in the past two years, our application reports how much your product will be sold for each month of the next two years with 4 different forecasting methods. These forecasting methods are "Exponential Smoothing","Double Exponential Smoothing","Regression Analysis" and "Deseasonalized Regression Analysis". MSE is calculated for each method and the method with the lowest error rate is determined. But you can get the reports of all other forecasting methods.

2. About Software

Our application has a user-friendly interface. We used the JavaFX library in the interface of our application and benefited from FXML technology. Besides, we preferred to use MongoDB in our program because of its flexibility, speed, power and compatibility with Java. It is very enjoyable to make the database management part of our application from MongoDB Atlas. Atlas made it…

Additional Resources / Info

  • JavaFX: We used the JavaFX library in the interface of our application and benefited from FXML technology.
  • MongoDB: We preferred to use MongoDB in our program because of its flexibility, speed, power and compatibility with Java.

Screenshots

Detailed sales forecasts for each month of the selected dataset are shown in the next four screenshots.

We developed this project with my school friend Yusuf Mert Ülgen.

We encourage you to read the README.md file, where we introduce our project in more detail.
Thank you for giving a time. Hope you like our project :)

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