A Neural Network Model for Market Share Prediction

Aim To present a new market share prediction model that can directly simulate the market choice mechanism without its context Methods A single hidden hierarchical neural network is used to build up a model It uses a back propagation(BP) algorithm to train the neural network Results and Conclusion This new model possesses a much higher precision and reliability when compared with other typical market share models by computed examples