灰關聯分析模型與灰預測模型係灰色系統理論中兩大重要灰色模型，自從發展以來，已廣泛地且成功地應用在不同領域上，其中亦包括營建管理領域。然而，隨著工程問題複雜性的提升，所得資訊的不確定性與不穩定性亦隨之增加，導致灰關聯分析模型與灰預測模型在其應用性上仍有可改進的空間。鑑此，本研究致力於提出創新的灰關聯分析模型與灰預測模型，以拓展灰色模型在不確定性及不穩定性環境下的應用。在灰關聯分析模型方面，主要導入灰數以及明考斯基距離函數的概念，建構新式灰數灰關聯分析模型，並延伸至聚類以及決策問題上，以有效地處理不確定性資訊。在灰預測模型方面，本研究主要修改其演算邏輯，包括背景值調整、特定解轉換及殘差修正等，以利於掌握不穩定系統發展的趨勢，以提升預測的精度。所有的創新灰色模型均透過營建工程相關問題的解決，驗證其有效性與實用性。

Grey relational analysis model and grey forecasting model are two kinds of important grey models in the grey system theory. Since these two models are proposed, they have been comprehensively and successfully employed in various fields, including the construction engineering area. However, owing to the increasing complexity of engineering problems and the following uncertain and instable information, the applicability of these two models should be further improved. Therefore, this study aims to propose novel grey relational analysis models and grey forecasting models in order to enhance their applicability under the uncertain and instable environment. In the aspect of creating novel grey relational analysis models, both the concepts of grey number and Minkowski distance function are mainly adopted. Besides, this study also extends the concepts of grey number grey relational analysis model to the clustering and decision problems. In the aspect of creating novel grey forecasting models, the algorithm of grey forecasting model is modified and integrated with residual recognition techniques to improve the forecasting precision. All new grey models are demonstrated their effectiveness and practicability by solving related practical problems of construction engineering.

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