Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/10156
標題: 以模糊粒子群演算法分辨地震場址效應
Classification of Site Effect Using Fuzzy C-means+ Particle Swarm Optimization
作者: 林旻學
LIN, MIN-HSUEH
關鍵字: 場址效應;Site effect;資料探勘;data mining.
出版社: 土木工程學系所
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摘要: 
地震發生時地表運動受到場址效應的影響,與當地土層參數有很高的相關性,由實測資料分析發現,場址的地震動放大效應並非只與現地地質有關,區域內地形也有影響。本研究中以觀察雙自由度系統受震反應變化,來判定台中科學園區附近10個測站場址效應相關性,並以遠近、大小規模不同地震之記錄輸入,探討是否具有同樣場址效應之分類。執行時,先以動力數值方法求得機台與基礎相對位移值,再引入Fuzzy C-means+ Particle Swarm Optimization資料探勘技術交叉識別各測站場址分類。由初步成果得知,近斷層較大之歷時加速度記錄可以有效反映場址效應,而遠斷層地震記錄因傳遞路徑過長,波形被模糊化,即使經放大或正規化,亦無法有效分類識別。整體而言,本研究提供了一套有別以往使用反應譜及土層剪力波速等方式探討場址效應的方法。

Site ground motion under earthquake is highly affected by local parameters. Through analyzing the excitation records, it has been found that both local geology and region landforms both play important roles. In this research relative difference of site effect, among 10 observation stations near Taichung Science Park, has been studied. Two degrees of freedom systems simulating precision machines are assumed to be subjected to various earthquakes. The relative displacements of the two masses have been obtained numerically. Then the results analyzed through Fuzzy C-means+ Particle Swarm Optimization data mining technology. Result shows that, records of near fault earthquake clearly identify site effects of different stations. On the other hand, records of far fault route excitation become too week to and can no longer contribute any meaningful identification.
URI: http://hdl.handle.net/11455/10156
其他識別: U0005-1207201313181100
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