過去幾十年，對於基礎建設的保護往往是邊坡災害的重要議題之一，可能的原因由地震、暴雨或其他人為活動所引起之邊坡災害。而近年來此現象則在集集地震後頃向於更糟糕，而由地震引起的邊坡擾動可能是其中原因之一。此外不只是地震的影響，對於土木工程師而言，全球暖化所引起的氣候劇烈變化皆是一個重要的議題及挑戰是我們現今要去面對的。因此本研究關注在邊坡穩定的議題上，根據前人的研究，Hoek-Brown 破壞準則比較Mohr-Coulomb破壞準則可提供較好的岩石邊坡穩定性評估。此外人工智慧技術提供了重複性工作的便利性並且可以維持其精準度。而本篇研究的目地是為了快速且大範圍的預測岩石邊坡穩定性及可靠度分析，而本研究根據三種不同的理論，極限分析法、AI技術及蒙地卡羅法以分析理解岩石邊坡穩定在地震情況。

For the past few decades, the slope disasters are often the issues for infrastructure protection. They can be caused by the earthquake, rainfall, and other human activities. Recently, the phenomenon is getting worse after Chi-Chi earthquake. The slope mass disturbance induced by earthquakes would be one of the factors. In addition to the earthquake effects, climate change as a result of global warming would be more an important problem (challenge) that civil engineers should face it from now on. Therefore, the attention of this study was paid to slope stability issue. According to the previous studies, Hoek-Brown failure criterion can provide better rock slope stability estimations than the conventional Mohr-Coulomb failure criterion. In addition, artificial intelligence (AI) technique brings the convenience for repetitive works and still maintain accuracy. The purpose of this study is to predict the rock slope stability and reliability by using three different concepts, namely as, Limit theorem, AI technique and Monte Carlo method for seismic rock slope stability problems.

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