An Application of Multiple Regression and Backpropagation Network for the Interdependence Model of Drainage-engineering-A Case study of Nantou Area，Taiwan.

• Main Authors: Chi-Ju Liu, 呂騏竹
• Other Authors: 翁祖炘
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/n9359g

碩士 === 國立臺北科技大學 === 材料及資源工程系所 === 94 === Project cost prediction or estimate has been an important,yet highly risky process.A mistakenly preliminary judgment will affect a whole project outcome.As far as drainage project is concerned,if given an exact prediction or estimate, the institution concerned may greatly cut down costs including purchasing,contact process,budgeting,bidding, and some other costs and losses incurring from estimate. In addition,the exact prediction or estimate can facilitate the project,beneficial for overall project costs and efficiency in checking and estimate.In this way,we may bring up a set improvement measure at the earliest day to make up for shortage. I personally gathered the budge plans for drainage improvement projects in the area of Nantou County,Taiwan during the period between 2000 to 2004,referred to specialists suggestions and applied multi-variables statistical analyses,including cluster analysis, one-way multivariate analysis of variance,multiple regression analysis and applying back-propagation network and other methods of mathematical analysis.It is expected the advantages and disadvantages of multiple regression analysis modes and back-propagation network modes are appraised by the acquired outcome,and applicable drainage project costs in Nantou area is then established to serve as reference for the relevant institutions,which may control over project costs and reduce project costs. The findings of the study show 1. multiple regression and back-propagation network is applied to conduct non-linear estimation,which proves good performance.The contracting expenditures of drainage project thus displays non linear distribution and its variables are higly correlated with the coefficients of variables.2. It is inferred from the comparison of Multiple Regression and Back-Propagation Network that MSE is applied with back-propagation network is better in terms of the performance estimation,and the application of MAPE shows high precision.This study consequently is feasible and good in reference.