本文選題：房屋震害損失評(píng)估 + 云計(jì)算�。� 參考：《中國(guó)地震局工程力學(xué)研究所》2017年碩士論文

【摘要】：房屋震害損失評(píng)估是地震災(zāi)害損失評(píng)估非常重要的一環(huán),對(duì)震后災(zāi)區(qū)救援和復(fù)建具有很大的指導(dǎo)意義和參考價(jià)值。傳統(tǒng)的房屋震害損失評(píng)估采取抽樣方法來采集數(shù)據(jù),然后基于這些具有一定代表性的數(shù)據(jù)來進(jìn)行評(píng)估,然而,用樣本數(shù)據(jù)來代替總體數(shù)據(jù)是一種“無奈之舉”,會(huì)在一定程度上削弱評(píng)估結(jié)果的準(zhǔn)確性。隨著信息時(shí)代的到來,各個(gè)行業(yè)領(lǐng)域的信息量快速增長(zhǎng),數(shù)據(jù)類型越來越復(fù)雜,大數(shù)據(jù)的概念就是在這樣的背景下被提出的。大數(shù)據(jù)不僅僅是數(shù)據(jù)量巨大,同時(shí)還兼具異構(gòu)性和價(jià)值性。但是要想發(fā)掘大數(shù)據(jù)所蘊(yùn)藏的價(jià)值性,需要便捷快速、經(jīng)濟(jì)的運(yùn)算工具。云計(jì)算是一種通過共享云端資源池來實(shí)現(xiàn)低成本高運(yùn)算的計(jì)算模式,目前,公認(rèn)是處理大數(shù)據(jù)的最佳利器。地震災(zāi)害評(píng)估方面的數(shù)據(jù)也在急劇增長(zhǎng)中,面對(duì)這種增長(zhǎng),傳統(tǒng)的計(jì)算和數(shù)據(jù)存儲(chǔ)方法在處理速度上越發(fā)顯得捉襟見肘。《中共中央國(guó)務(wù)院關(guān)于進(jìn)一步加強(qiáng)城市規(guī)劃建設(shè)管理工作的若干意見》指出要“推進(jìn)城市智慧管理。加強(qiáng)城市管理和服務(wù)體系智能化建設(shè),促進(jìn)大數(shù)據(jù)、物聯(lián)網(wǎng)、云計(jì)算等現(xiàn)代信息技術(shù)與城市管理服務(wù)融合,提升城市治理和服務(wù)水平�！钡卣馂�(zāi)害評(píng)估也需要推進(jìn)智慧管理,將現(xiàn)代信息技術(shù)手段引入到地震災(zāi)害評(píng)估等相關(guān)領(lǐng)域,以此得到更好的發(fā)展。論文主要做了以下幾項(xiàng)工作:1)綜述大數(shù)據(jù)、云計(jì)算在地震數(shù)據(jù)處理領(lǐng)域運(yùn)用的國(guó)內(nèi)外發(fā)展現(xiàn)狀。通過大量的資料查詢以及分析對(duì)比工作,最終選定本文的云開發(fā)平臺(tái)為Hadoop。同時(shí)結(jié)合本文數(shù)據(jù)存儲(chǔ)以及計(jì)算速度的需求,明確了本文采用的云計(jì)算三項(xiàng)技術(shù):MapReduce編程模型、HDFS分布式文件系統(tǒng)以及HBase非關(guān)系型數(shù)據(jù)庫,并對(duì)這三項(xiàng)相關(guān)技術(shù)進(jìn)行了必要的介紹。2)詳細(xì)分析了目前傳統(tǒng)房屋震害損評(píng)估方法存在的不足,結(jié)合房屋震害數(shù)據(jù)采集手段不斷進(jìn)步的發(fā)展趨勢(shì),設(shè)計(jì)了一種理想化的基于大數(shù)據(jù)應(yīng)用云計(jì)算技術(shù)評(píng)估詳實(shí)房屋震害損失的方法,重點(diǎn)是用全數(shù)據(jù)參與評(píng)估。并且完成以下幾部分設(shè)計(jì):a)數(shù)據(jù)存儲(chǔ)方面,設(shè)計(jì)出合理的便于存儲(chǔ)以及進(jìn)行數(shù)據(jù)操作的HBase數(shù)據(jù)表結(jié)構(gòu)。并且完成了數(shù)據(jù)批量錄入HBase的程序設(shè)計(jì)。b)數(shù)據(jù)處理部分:將整個(gè)評(píng)估過程進(jìn)行合理的拆分,設(shè)計(jì)出高效可靠的算法流程,并通過MapReduce程序來實(shí)現(xiàn)。3)將大量數(shù)據(jù)導(dǎo)入HBase數(shù)據(jù)庫,在數(shù)據(jù)庫相同的條件下,分別運(yùn)用云計(jì)算集群和傳統(tǒng)單機(jī)模式計(jì)算房屋震害損失值,比較本評(píng)估方法運(yùn)用兩種計(jì)算工具的計(jì)算速度。
[Abstract]:Building damage assessment is a very important part of earthquake disaster loss assessment, which has great guiding significance and reference value for disaster relief and reconstruction after earthquake.The traditional method of building damage assessment is to collect data by sampling method, and then evaluate it based on these representative data. However, it is "helpless" to replace the overall data with sample data.To some extent, the accuracy of the evaluation results will be weakened.With the arrival of the information age, the amount of information in various industries is increasing rapidly, and the data types are becoming more and more complex. Big data's concept is put forward under this background.Big data is not only a huge amount of data, but also heterogeneity and value.But in order to explore the value of big data, need convenient and rapid, economic computing tools.Cloud computing is a kind of computing mode which can achieve low cost and high operation by sharing cloud resource pool. At present, cloud computing is recognized as the best weapon to deal with big data.Data on earthquake disaster assessment are also growing dramatically, and in the face of this growth,The traditional methods of calculation and data storage are more and more overstretched in processing speed. "some opinions of the CPC Central Committee and the State Council on further strengthening the management of urban planning and construction" pointed out that "promoting urban intelligent management".Strengthen the intelligent construction of urban management and service system, promote the integration of modern information technology such as big data, Internet of things, cloud computing and urban management services, and improve the level of urban governance and services. "Earthquake disaster assessment also needs to promote intelligent management and introduce modern information technology into earthquake disaster assessment and other related fields in order to get a better development.This paper summarizes the development of big data, cloud computing in the field of seismic data processing at home and abroad.Finally, the cloud development platform of this paper is chosen as Hadoop through a lot of data query and analysis and comparison work.At the same time, according to the requirement of data storage and computing speed in this paper, three technologies of cloud computing, namely: MapReduce programming model, HDFS distributed file system and HBase non-relational database, are defined in this paper.At the same time, the necessary introduction of these three related technologies. 2) analyzes in detail the shortcomings of the traditional methods for evaluating the damage of buildings, and combines with the developing trend of the means of collecting data on the earthquake damage of buildings.An idealized method based on big data's application of cloud computing technology is designed to evaluate the damage loss of detailed buildings, with the emphasis on full data participation.At the same time, the following several parts are completed to design the HBase data table structure which is convenient to store and operate.And completed the program design of data batch input into HBase. B) data processing part: the whole evaluation process is divided reasonably, the efficient and reliable algorithm flow is designed, and a large amount of data is imported into HBase database through MapReduce program.Under the same database condition, the cloud computing cluster and the traditional single-machine model are used to calculate the damage value of buildings, and the calculation speed of the two computing tools is compared in this evaluation method.
【學(xué)位授予單位】：中國(guó)地震局工程力學(xué)研究所
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：P315.9;TP311.13

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本文編號(hào)：1735925