An Empty Nester Recognition Model Based On a Feed Forward Neural Network

With the trend of aging of society, the number of empty nesters is rising, which has become a social problem that cannot be ignored. In this paper, two empty nester recognition models were presented based on the analysis of calling list and user information table. Based on the normal data, the empty nesters and their children's number can be identified by a recognition function. When the properties of a user are not adequate, recognition function cannot be applied to identify it. Feed forward neural network algorithm is used to solve this problem. The recognition accuracy rate can reach 73.3% after training the network. Based on the research, certain approaches can be made to improve the situations, which is beneficial to the development of a harmonious society.