DizhenLiang / LSTM_ARM

Time Series Prediction Application

Welcome

Welcome to the Time Series Prediction Application, a web-based tool that utilizes Association Rule Mining (ARM) combined with a Long Short-Term Memory (LSTM) machine learning model to predict time-series data. It is designed to be user-friendly and efficient, providing valuable insights for decision-making in various fields such as economics, healthcare, and science.

Team Members

• Liang Dizhen
• David Chyun Roo Lee
• Muhammad Abdullah Akif

Table of Contents

1. Introduction
2. Setup and Installation
3. Usage
4. Testing and Quality Assurance
5. User Guides
6. Technical Documentation

Introduction

The Time Series Prediction Application is designed to predict electricity load using historical data. It provides a simple interface for uploading datasets, initiating predictions, and visualizing results.

Setup and Installation

To set up and install the Time Series Prediction Application, follow these steps:

1. Ensure you have Python 3.7+ installed on your system.
2. Clone the repository to your local machine.
3. Set up a virtual environment and activate it.
4. Install the dependencies listed in requirements.txt using pip install -r requirements.txt.

Usage

To use the application:

1. Start the Flask server by setting the FLASK_APP environment variable to app.py and running flask run.
2. Access the application through your web browser at http://127.0.0.1:5000.
3. Follow the step-by-step guide provided in the User Guides to upload datasets, run forecasts, and view results.

Testing and Quality Assurance

The application has undergone extensive testing to ensure it meets product requirements and is bug-free. The testing approach includes both automated and manual testing methods, focusing on functional and non-functional requirements. For details on the testing procedures and results, refer to the [Software Test/QA Report](MCS23 FIT3162 Software Test_QA Report.pdf).

User Guides

For comprehensive user guides, including accessing the application, interface overview, step-by-step guides, and tips for best results, refer to the [User Guides](MCS23 FIT3162 User Guides.pdf) document.

Technical Documentation

For technical details, including prerequisites, installation steps, running the application, using the application, and troubleshooting, refer to the [Technical Guide](User Guides.pdf).