Market Price Forecaster
Predict commodity prices using deep learning Artificial Neural Network
Model: ANN (Deep Learning) | R² Score: 0.9396Market Parameters
Enter market and environmental data
📖 How It Works
Our price forecaster uses an Artificial Neural Network (ANN) with architecture 64→32→16→1 neurons, dropout regularization (0.2), and Adam optimizer—a sophisticated deep learning model trained on 4,380 time-series records (5 years, 2020-2024) to predict commodity prices 30 days ahead.
📊 Price Prediction Factors:
- 🌾Commodity Type & Region: Rice, Corn, Sugarcane across major producing regions
- 📈Production Volume: Current harvest levels and seasonal trends
- 🚢Trade Volumes: Import/export data affecting supply and demand
- 🌡️Climate Indicators: Temperature, rainfall, and seasonal weather patterns
- ⏰Lag Features (Price History): Past prices at 1, 7, and 30 days capture market momentum and trends
- 📅Temporal Features: Month and day-of-year encode seasonal patterns (harvest cycles)
💹 Supported Commodities:
🌾 Rice (all varieties)🌽 Corn (yellow & white)🎋 Sugarcane
📊 Model Performance:
R² Score
0.9396
Excellent Fit
MAE
₱1.87
Per kg
RMSE
₱2.43
Accuracy
✓ Trained on 4,380 price records (5 years: 2020-2024)
✓ Network: 64→32→16→1 with dropout=0.2, Adam optimizer
✓ Early stopping at epoch 52 for optimal generalization