Abstract for: System Dynamics and Genetic Artificial Neural Network Models for the Monitoring and Early Warning of Urban Housing Market

The problem of empty houses in Taiwan continues to concern the public. The Government currently conducts housing survey to detect the number of empty houses every year. But, no systematic analysis of the monitoring and early warning programme has been undertaken to improve the situation. This study formulated dynamics and genetic artificial Neural Network models for the monitoring and early warning system stimulating. Several strategy scenarios were conducted. The research findings showed that economic strategy has a more positive and profound impact than financial one; combined strategy often has a better policy assessment compared to a single strategy. The method developed in this study is a comprehensive and systematic approach to achieve the sound housing market in Taiwan. Keywords: System dynamics, Genetic artificial neural network, Monitoring and early warning, Urban housing market