A complete guide to understanding the LSTM-based AI prediction system
AI Crypto Predictor uses an LSTM Neural Network to analyze real-time market data and generate price predictions and trading signals for 50+ cryptocurrencies.
The system collects real-time price data from Binance WebSocket and Bitget API. Each data point includes:
200 price points are required before LSTM activates.
The system extracts 6 key features from the data:
The Long Short-Term Memory (LSTM) model is a deep learning architecture designed for time-series prediction.
The system generates:
Binance/API β Price Data β Price History (200+ points) β Feature Extraction β LSTM Model β Prediction β Signal β Chart
β
MySQL Database
β
localStorage (cache)
LSTM generates predictions every 15 seconds with 70-85% directional accuracy. Each prediction includes price target, confidence score, and wave strength analysis.
BUY/SELL signals with 11 threshold levels (0.05% to 1.0%). Signals are color-coded and include confidence scores and expected returns.
Color-coded prediction lines show market volatility in real-time with 4 wave strengths: Calm, Moderate, Strong, and Extreme.
Live RSI, MACD, Bollinger Bands, Stochastic, Volume Profile, and ATR indicators for comprehensive market analysis.
Auto-save to database every minute. Export/import predictions, training data, and model weights. 300 signals in memory, 150 visible in chart.
Supports 50+ cryptocurrencies including BTC, ETH, DOGE, SOL, PEPE, and more. Each coin has its own LSTM model and data storage.
The prediction line is color-coded based on market volatility:
Low volatility, sideways market
Normal market movement
High volatility, strong signals
Extreme volatility, major moves
Trading signals with confidence
Best threshold for signals
The system analyzes multiple technical indicators in real-time:
Relative Strength Index (0-100) - Identifies overbought (>70) and oversold (<30) conditions.
Volatility bands (20,2) - Shows price position relative to upper and lower bands.
Moving Average Convergence Divergence - Identifies trend direction and momentum changes.
%K and %D lines - Identifies momentum and potential reversal points.
Buy/Sell volume ratio - Shows market sentiment and accumulation/distribution.
Average True Range - Measures market volatility and helps set stop-loss levels.
The 11 precision levels control signal sensitivity:
The system collects 200 price points (about 50 minutes) before LSTM activates. This ensures the model has enough historical data for accurate pattern recognition.
LSTM uses deep learning neural networks for pattern recognition. Algorithmic is a fallback using mathematical formulas when LSTM is not ready (less than 200 points).
The system achieves 70-85% directional accuracy with over 7,500+ predictions. Confidence scores (0-100%) indicate reliability.
Each coin has separate data stored. Switching coins loads that coin's data and LSTM model. The system collects data per coin independently.
π΅ Calm (<0.02%) = Low volatility
π’ Moderate (0.02-0.05%) = Normal movement
π‘ Strong (0.05-0.1%) = High volatility
π΄ Extreme (>0.1%) = Very high volatility
β 0.5% is the optimal balance between accuracy and frequency. Lower = more signals (0.05-0.3%), Higher = fewer but stronger signals (0.7-1.0%).