Applied Mechanics and Materials Vols. 368-370

Abstract: Since 2012, Taiwan enforces real price login, people can reference data and understand the changing price of various regions. The housing price of this study, therefore, is designated by unit price of trading contract. Taipei City, one of five municipalities in Taiwan, is found the unit price of trading contract is the most than others in an upward trend in its database from the third quarter of 2007 to the second quarter of 2012 (total twenty seasons). So, this study explores the relationship with others between unit price of trading contract overall in Taipei and unit price of trading contract of 12 districts. It is going to use autonomic architecture model with the ability of genetic algorithm operate tree (GAOT) to find out the best combination of variables and establish the relationship mode between each other. It also can assess overall real estate trends in Taipei City by important changing of districts. Research statistical analysis shows correlation coefficient (CC) for unit price of trading contract is 0.98 in Daan district and overall Taipei City. The result shows a high degree of correlation. After GAOT operator, besides, the establish assessment model could be found. It only uses unit price of trading contract of four districts. The unit price of trading contract of overall Taipei can be known. The coefficient of determination (R²) is up to 0.996 and root mean squared error (RMSE) is 0.406. The results are better than multiple linear regression (MLR) (R²=0.994, RMSE=0.490) and appear that GAOT can predict accurately of overall Taipei. It exist the relationship with each other between four districts and Taipei. In other words, the trend of variable is in coincide circumstance. The advantage of unit price of trading contract can be later used, therefore, this kind of mode to statistic four districts. The forecasting process for unit price of trading contract overall Taipei engages the government and civil society to assess overall real estate market of urban area.

Abstract: According to the status of the current engineering construction field in our country, in order to adapt to the requirements of engineering construction project risk evaluation, this paper discuss establishing a reasonable risk evalluation index system and a model of effective risk evaluation. By analyzing the advantages and disadvantages of the general model of risk evaluation, determine the risk evaluation model combined with BP neural network with AHP; secondly,establish a risk evaluation index system; once again,illustrate the method which represents the correlation between evaluation index system and the degree of risk; finally, establish a reasonable BP neural network model.Key Word:Evaluation index; Risk Evaluation ;AHP;BP Neural Network; Model Construction