Cat-NN for Traffic Forecasting

Cat-NN for Traffic Forecasting

Cat-NN (Categorical Neural Network) is a deep learning model that uses categorical data to predict traffic patterns. It has shown promising results in accurately forecasting traffic flow and congestion levels.

By analyzing historical traffic data and incorporating categorical variables such as time of day, weather conditions, and special events, Cat-NN can provide accurate predictions for traffic forecasting, helping to improve traffic management and reduce congestion on roadways.