The paper analyses the commodity house price, land price, building and equipping cost and developer’s profit around “8.31”, and compares the ratio of land price to house price. We find that the ratio of land price to house price is stable. We analyses the factors that affect house price based on our analysis. We use examples to show that land price, building and equipping cost, developers’ expected profit is the main factors that affect house price. We analysis the ratio of land price to house price around “8.31” based on the difference of building cycle, we find that the ratio of land price to house price reduces with the average building cycle increased (This is innovation of this paper), the ratio is about 10% or 20%. Then we use gray relation degree to analysis the factors affecting the house price, show that per income, population and per inhabitant condition are the main factors affecting land price of ShenZhen. Analyzed land price building and constructing cost, we find out expected profit of developer is the main cost factors affecting real estate price through the case.

This paper explains the current situation of technology development in Chinese construction industry, which is primarily based on the relative data from 1998 to 2002, it discusses the effect on construction industry from several aspects such as: technical elements, human cost, capital investment, technology innovation, and the article points out present problems in the process of enhancing technology improvement in this area.

Building energy efficiency economy system is a complex adaptive system comprised of multi beneficial agents that their inner and outer relationships affect the system developing orientation together. This paper researches on the co-evolvement mechanism among different system agents using Multi-Agent System and simulation methods. After analyzing the characters and behaviors of different agents, SWARM simulation simulates the future tendency on executing building energy efficiency policy and efficiently solves the limited historical data.

This study analyzes the chaos emerging mechanism through using logistic model according to the nonlinear character of Chinese real estate business cycle. The chaos emerging hypothesis is validated by the data in Chinese real estate market through nonlinear regression method. On the basis of comparing the different characters before and after entering the chaotic state, it can be found that the real estate bubble is prone to expanding and even breaking in chaotic field. And the main control factor is price-elasticity index of demand.

Comprehensive analysis is made about the factors that affect the Real Estate price. Main factors are summarized such as supply and demand, economy, cost, administration, society, environment and others. Because it is difficult to quantify the influence of social, administrative and other factors, factors such as supply and demand, economy, cost, environment are considered as main target of our study. Based on the data between 2000~2004 in Shenzhen, Grey incidence analysis is made about the main factors influencing the Real Estate price, which are given as results: The construction level of municipal infrastructure, consumption level per capita and cost of housing are principal factors that influence of the Real Estate price in Shenzhen, secondly land price, income level per capita, population size and dwelling level per capita, etc. again speed of economic development, price level and supply level of housing, etc.