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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/68662

    Title: 基於支持向量機及模糊推理之地震預警系統研製;Implementation of Earthquake Early Warning System Based on Support Vector Machine and Fuzzy Inference
    Authors: 王崴弘;Wang,Wei-Hung
    Contributors: 通訊工程學系
    Keywords: 地震預警系統;加速度感測器;支持向量機;模糊推理;EEW System;G-Sensor;Support Vector Machine;Fuzzy Inference
    Date: 2015-07-29
    Issue Date: 2015-09-23 13:58:22 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 台灣位於歐亞大陸板塊 (Eurasian Plate) 與菲律賓海板塊 (Philippine Sea Plate) 的交接處,屬於環太平洋火山帶 (Ring of Fire) ,容易因板塊移動而造成地震,是世界上地震最為頻繁的區域之一,每每造成人民生命財產的損失。一旦地震發生時,大多數民眾只能在當下做最本能的反應,不容易快速得知地震資訊,甚至提早得知地震即將發生,所以,地震預警系統 (Earthquake Early Warning System, EEWS) 的開發與研究,就變成一個迫切需要討論的議題。
    因此,本論文以全新的視角審視地震預警系統,並以通訊領域的觀點出發,提出利用加速度感測器 (G-Sensor) ,結合支持向量機 (Support Vector Machine) 、模糊推理 (Fuzzy Inference) 等理論的演算法,並實作地震預警函式庫。由於加速度感測器目前的應用廣泛,例如:智慧型手機、平板電腦、硬碟等等我們每天都會接觸的設備皆有內建,所以能將配有加速度感測器的裝置都視為一個小型的地震觀測站,只要擁有上網的能力並運行包含地震預警函式庫的APP或電腦程式,就能以最低的成本形成最大的地震觀測網,一舉解決上述的三個問題,發揮地震預警系統最大的能力。;Taiwan is located in a seismically active zone and faces the problem of a large number of earthquakes. Many disastrous earthquakes usually cause the loss of lives and properties over the years. Therefore, how to design a series of preventative measures and reduce the risk of damages caused by earthquakes is an important issue. So far we still do not have a better way to get earthquake warning immediately. As a result, the Earthquake Early Warning System (EEWS) would be a useful tool and has become the urgent need of human beings.
    Nowadays countries neighboring the Ring of Fire put a lot of efforts and resources on investigating the EEWS. Among them, Japan, The United States of America, and Taiwan have the most abundant achievements. Constructing the EEWS has some common problems. Firstly, the need of the special equipment for seismic wave sensing costs highly. Secondly, the number of earthquake detection stations cannot increase arbitrarily due to the lack of funds. Thirdly, people are not familiar with the EEWS. Until now, people get the earthquake news from television, radio stations or social APPs. The EEWS does not fully come into our lives.
    In this thesis, we propose a new algorithm and architecture of the EEWS named as the EQ-system. The hardware part of EQ-system is a G-sensor for detection. The software part of EQ-system is a library of earthquake early warning called LibEQ. LibEQ combines several theories such as Support Vector Machine, Fuzzy Inference and so on. We can build a biggest earthquake detection network with low cost. People can get earthquake alarm by APP. Consequently, for earthquake early warning, EQ-system can produce the best possible results.
    Appears in Collections:[通訊工程研究所] 博碩士論文

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