隨著國內營造業的專案工程日益大型化、複雜化,導致工程最終成果不確定性增加,而學界及業界人士普遍認為專案先期規劃評估階段對專案的成果有相當程度之重要性。因此,本研究將引用先前研究所建立的台灣營建業之建築專案先期計劃階段範圍定義評析指標,針對台灣營建業之建築專案作訪談及分析。透過邏輯斯迴歸模式(Logistic)及結合類神經網路集成學習之拔靴集成法(Bootstrap Aggregating)和多模激發法(AdaBoost)等兩種不同概念的預測方法,應用在建構PDRI 分數對其建築專案成本與時程績效預測模型,來發展一套較適切於台灣建築專案先期計畫階段之預測模式。
As the building construction projects become larger and more complex, researchers and the industry practitioners both recognize the importance of early planning and its potential impact to final project outcome. Nevertheless, the preproject planning practice varies significantly throughout the industry. This research incorporates Project Definition Rating Index (PDRI) as part of the survey questionnaire to investigate the current practice of preproject planning for the building construction in Taiwan. Information from a total of 92 building projects is collected to study the relationship between the level of preproject planning and project performances (cost and schedule). With the PDRI scores as the independent variable and project performances (cost and schedule separately) as the dependent variable, statistical methods (Logistic Regression) and Artificial Neural Network (Bootstrap Aggregating and AdaBoost) methods are used to develop prediction models.