土壤液化一直是大地工程中很重要的課題，因此也發展出許多不同的液化評估方法，其中簡易經驗評估法為工程界所常利用。Nemat-Nasser and Shokooh在1979年提出地震能量消散與孔隙水壓增量有關的概念，此後，根據能量觀點來探討液化潛勢之可能性便成為液化評估主要的研究方向之一。本研究參考Berrill and Davis（1985）提出的非線性能量消散模式，以孔隙水壓增量與消散能量間之非線性關係為基礎，運用大地工程界常用之反覆三軸試驗資料推算遲滯圈液化能量，再以類神經網路自動試誤程式經4000次自動試誤後，求得網路模式之最佳架構。本研究以類神經網路液化能量模型配合九二一地震之現場試驗數據，運用多變量分析中之判別分析方法訂定液化分界線並計算其液化機率，建立液化評估之經驗準則。研究結果顯示，以實驗室試驗資料建立之類神經網路液化能量模型，對於現地資料液化判定之成功率約為91%，顯示本研究所提出的能量式液化評估模式有其合理之評估能力，可擴展應用於大地工程實務設計時之參考。

The soil liquefaction is always the important topics in the discipline of Geotechnical Engineering. Many methods related to evaluation of the potential of the soil liquefaction have been developed. However, the Simplified Empirical method the one that is much more common used both in academic and in practice.
Since Nemat-Nasser and Shokooh in 1979 proposed the principle of relations between dissipation of seismic energy and the increment of pore water pressure during earthquake, the method on the basis of the seismic energy concept has become the mainstream on evaluation of the soil liquefaction potential.
By referring the principle of the nonlinear energy dissipation that proposed by Berrill and Davis in 1985 and the liquefaction energy that calculated from the hysteresis loop obtained from the soil cyclic triaxial tests in laboratory, the neural network model is used in this study to simulate the liquefaction energy in field. The framework of the model is found by the auto trial and error process. And by associating with the statistical discriminant method, the critical line judging the occurrence of the soil liquefaction can be developed. With the 91% of success rate of the liquefaction assessment, the proposed neural network model is fair reasonable and suitable for the practice in geotechnical engineering.

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