A Fuzzy Logic Expert System For Stock Prediction

📋 Table of Contents

1. 🤖 Introduction
2. ⚙️ Tech Stack
3. 🔋 Features
4. 🤸 Quick Start
5. 🔗 Links

🤖 Introduction

The Fuzzy Logic Expert System for Stock Prediction utilizes fuzzy logic principles to predict stock market trends. This project aims to provide a robust and intuitive tool for investors and analysts to make informed decisions based on fuzzy logic inference. It calculates a price increase or a decrease based on stock input variables.

⚙️ Tech Stack

• Python
• scikit-fuzzy
• NumPy
• Pandas
• Matplotlib
• Flask (for web integration)
• HTML/CSS/JavaScript (for front-end)

🔋 Features

👉 Stock Trend Prediction: Predict future stock trends using fuzzy logic inference.

👉 Rule-Based System: Implement custom rules for stock prediction based on historical data and expert knowledge.

👉 Graphical Representation: Visualize inference steps and results through detailed charts and graphs.

👉 Flexible Membership Functions: Define custom membership functions for various input variables (e.g., profit, roa).

👉 Web Interface: Interactive web interface for inputting data and viewing predictions.

👉 Modular Design: Easily extendable and modifiable code structure.

👉 Dataset Cleanup and Comparison: Use of a known dataset to calculate and compare results.

🤸 Quick Start

Follow these steps to set up the project locally on your machine.

Prerequisites

Make sure you have the following installed on your machine:

• Python
• pip
• Git

Installation

Install the project dependencies using pip in the folder.

pip install flask
pip install numpy
pip install scikit-fuzzy
pip install pandas
pip install matplotlib

Running the Project

1. Interface

   python app.py

2. Dataset Code

   python StockPrediction.py

Open http://127.0.0.1:5000 in your browser to view the project.

🔗 Links

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