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Title: 以模糊類神經網路結合CPT案例評估土壤液化潛能
Combine Neuro-Fuzzy Networks and CPT Results to Assess Liquefaction Potential
Authors: Jr-Ren Lu
Contributors: NTOU:Department of Harbor and River Engineering
Keywords: 土壤液化;CPT;類神經模糊系統;群聚分析;臨界曲線
liquefaction;CPT;Neuro-Fuzzy system;clustering algorithm;limit curve
Date: 2004
Issue Date: 2011-06-30T07:32:32Z
Abstract: 過去數十年來,全世界有許多國家,例如,中國大陸、日本、美國、智利與中美洲等各國皆發生許多地震而引發土壤液化,也因此造成了許多無辜生命死亡與財產的損失。台灣地區尤以1999年的921集集地震引起的土壤液化,造成了結構物損毀與人員的傷亡。集集大地震亦使部分地區產生液化噴砂現象,並引致地盤下陷龜裂及房屋沉陷等危害,其中,集集大地震對於中部地區造成多起土壤液化災害,觀測所得以員林、霧峰、南投與彰濱工業區等區域最為嚴重,然而這些豐富、珍貴的資料、亦可提供給研究學者們建立本土化之液化分析模式。 本研究收集文獻之CPT試驗之液化案例,國外案例201筆,國內案例199筆,利用類神經模糊系統結合群聚分析來進行液化案例的研究,並且藉由傳統CPT液化潛能評估法輔助類神經網路的輸入參數的決定。研究結果發現本研究以不同參數組合評估液化指數模式成功率均為90%左右,較以傳統分析方法所得成功率僅有69%左右為佳。經模糊群聚類神經網路以逼近方式找出臨界液化曲線,建立液化阻抗參數與反覆應力比之對應關係,期能適用於本土案例之應用。
There are hundred cases of ground failure and damage to structures due to liquefaction during earthquakes in China, Japan, Chile, Central America, and the United State. Recently in 1999, considerable amount of damages had been caused in central part of Taiwan by Chi-Chi earthquake induced liquefaction. Numerous studies have been conducted to evaluate liquefaction potential. In this study, a reliable Cone Penetration Test data are gathered with a wide range of parameters. These data are incorporated in a Neuro-Fuzzy system that is based on clustering algorithm and neural network to evaluate earthquake induced liquefaction potentials. The results show that artificial neural network models has a better success rate of 90% than those of traditional one with 69% of the success rate for evaluating liquefaction potential. Based on study results, a simplified CPT-based limit curve for evaluating liquefaction potential is also developed.
URI: http://ethesys.lib.ntou.edu.tw/cdrfb3/record/#G0M92520004
Appears in Collections:[河海工程學系] 博碩士論文

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