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.

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.

Building energy efficiency (BEE) economic incentive system is an enormous system of multi-agent, which includes government departments, design institutes, construction units, real estate development enterprises, purchasers and energy service companies etc. It has a widely internal relationship and a character of multi-layer, multi-function, dynamic, open and mutually learning, so it is conformed that this system has the basic character of complex system. As a rational method to solve the problem of complex system, Cellular Automata (CA) can analyze the grid dynamic model which is not only discrete in temporal and spatial aspects but also partial in temporal consequence and spatial mutual relationship. Under some certain simple units and regulations, CA can simulate the complex system veritably. With the bottom-up modeling method of CA, this study establishes an evolutionary model of multi-agent for BEE economic incentive system in China through analyzing the complex character of this system. Based on the analytic result of evolving processes, it is recognized that the influence factors of promoting BEE economic incentive policy involves behavior preference, macro environment factors and different actual conditions of local regions.

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.

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.