Here are the key points about time series forecasting and neural networks:
- Time series forecasting is important for predicting future values based on historical data patterns. It has applications in domains like business, economics, science, and engineering.
- Neural networks are a popular machine learning technique used for time series forecasting. They can identify complex patterns in historical time series data.
- A neural network builds a mathematical model based on example inputs (time series training data) to make predictions or decisions without being explicitly programmed.
- The network learns by considering examples supplied to it through an iterative process, and adjusting the weights between nodes accordingly to optimize predictions.
- For time series forecasting, neural networks can capture nonlinear relationships