Design And Implementation Of The Real Estate Early Warning System

The Real Estate industry is a guiding industry for domestic, it is the foundation of the national economy and a real reflection of national economic level. If healthy developed, it would guarantee the benign development of national economy. In contrast, if unbalanced developed, its pattern may easily cause great harm to social and national development and won't have a long-term growth potential. In recent years, the illusion of prosperity has appeared in domestic Real Estate industry, making the early warning of Real Estate become a new researching hotspot for many scholars. So far, different methods of evaluation and analysis were achieved by many experts and scholars.Considering the current situation of domestic Real Estate industry and the rapid development of machine learning and artificial intelligence technology, the article was aimed at establishing a scientific intelligent early-warning system in the Real Estate industry. According to the actual situation of domestic Real Estate industry, as well as the causes and theory of Real Estate fluctuation, the article analyzed factors affecting the Real Estate market from both internal and external sides. Thus it built a scientific index system of Real Estate.To eliminate the shortcomings of the existing early-warning system of Real Estate, the early-warning model of Real Estate market was set up based on the SVM of machine learning. By matlab simulation experiment, the results showed that the early-warning model of Real Estate market was feasible and effective in the practical application.Finally, we designed and developed early-warning system of the Real Estate. Meanwhile, the aforementioned early-warning model based on SVM was applied in this system. When the system is implemented on the line, the data of Real Estate could be intelligently collected, selected and forecasted, which would enable managers to check the information of local Real Estate projects at anytime and government sectors to monitor the Real Estate market effectively for timely forecast and decision, so that the industry would become more transparent.