This repository contains the simplified frontend for my capstone project:
“Automated Time Series Forecasting: Using Hybrid Forecasting Approach.”
Refer to this link for the research's extended abstract. You can read the full document and explore my other projects.
Originally, the full system was implemented using PHP’s Laravel framework (serving Blade templates) alongside a dedicated Python Flask application for the core forecasting logic.
For this simplified version, I’ve rewritten the backend with a clean separation between backend and frontend:
- Frontend: React.js
- Backend: Python Flask (lightweight and fast for development)
This React web application allows the user to interact with the hybrid time series forecasting model that was developed during the research. Specifically, it has the following:
- Input time series data
- Preprocess the data
- Allow modification on forecast options
- Forecast time series base on specified steps
- Provide AI explanation on the results.
- Paulet Crysline Pajo – Project Leader
- Jun Jun M. Zaragosa – Lead Programmer
- Leynard Guinumtad
- Janeil Capales
- Camile Marticio
- Jann Daerick Finulliar