Impact Factor

7.883 Call For Paper

Share on

Author(s):

Sivasangari.J | Thota Vinod Kumar | Thota Bharath | Sriramsetty Mallikarjuna | T. Hari Venkata Sudheer Babu
Keywords:

Cryptocurrency, Price Prediction, Machine Learning, LSTM, GRU, XGBoost, Relative Strength Index (RSI), Technical Analysis, Streamlit Dashboard, Time Series Forecasting.
Abstract:
Cryptocurrency Markets Are Highly Volatile And Change Rapidly, Which Makes Price Prediction And Decision- Making Difficult For Investors. This Project Presents A Live Cryptocurrency Market Dashboard That Provides Real-time Market Visualization Along With Machine Learning-based Price Prediction And An RSI-based Buy/Sell/Hold Signal System. The System Collects Live Cryptocurrency Data Using The CoinGecko API And Processes It For Analysis. Three Models— LSTM, GRU, And XGBoost—are Used To Predict Future Prices, And Their Performance Is Evaluated Using Metrics Such As MAE, MSE, RMSE, And MAPE. In Addition To Prediction, The Dashboard Calculates The Relative Strength Index (RSI) To Generate Trading Signals That Help Users Understand Whether To Buy, Sell, Or Hold A Cryptocurrency. The Dashboard Is Developed Using Streamlit And Plotly To Provide An Interactive And User-friendly Interface. By Combining Live Data, Machine Learning Models, And Technical Indicators, The Proposed System Acts As A Practical Tool For Cryptocurrency Market Analysis And Basic Investment Decision Support.