本文選題：客流量預(yù)測　切入點：世園會　出處：《青島理工大學(xué)》2013年碩士論文

【摘要】：隨著互聯(lián)網(wǎng)的普及,旅游業(yè)的蓬勃發(fā)展,互聯(lián)網(wǎng)技術(shù)廣泛應(yīng)用到旅游業(yè)中。目前,互聯(lián)網(wǎng)作為重要的信息發(fā)布平臺,許多旅游景區(qū)的相關(guān)人員利用互聯(lián)網(wǎng)發(fā)布一些旅游信息,廣大旅游者在出行前也通過互聯(lián)網(wǎng)獲取旅游信息。鑒于各國學(xué)者關(guān)于互聯(lián)網(wǎng)技術(shù)的社會行為研究表明,互聯(lián)網(wǎng)熱詞的網(wǎng)絡(luò)搜索量與社會行為具有一定的聯(lián)系,引導(dǎo)著實際的社會行為,其中包括旅游行為。為推進網(wǎng)絡(luò)行為的研究,百度和谷歌分別推出了百度指數(shù)和谷歌趨勢兩大產(chǎn)品,為廣大學(xué)者查詢相關(guān)熱詞的網(wǎng)絡(luò)搜索量提供了便利。 本文通過運用定性、定量、實證研究等方法,證明熱詞的網(wǎng)絡(luò)搜索量與世園會的實際客流量具有相關(guān)性。本文基于網(wǎng)絡(luò)搜索行為構(gòu)建世園會客流量預(yù)測和預(yù)警模型,通過借鑒有關(guān)網(wǎng)絡(luò)行為方面的研究成果,構(gòu)建世園會網(wǎng)絡(luò)搜索熱詞的指標體系,利用谷歌趨勢提供的網(wǎng)絡(luò)搜索量,運用回歸分析、灰色理論預(yù)測和預(yù)警世園會的客流量,并通過實證驗證所構(gòu)建模型具有實用性。本文主要研究內(nèi)容包括以下六個方面： (1)闡述本文的研究背景和研究意義,分析國內(nèi)外基于網(wǎng)絡(luò)搜索行為的研究現(xiàn)狀,提出本文的主要內(nèi)容、研究框架、研究方法和技術(shù)路線。 (2)分析本文的相關(guān)理論,包括網(wǎng)絡(luò)搜索行為和數(shù)據(jù)處理。首先介紹谷歌趨勢的功能及應(yīng)用方法,然后介紹灰色系統(tǒng)理論,包括原理、特點和主要內(nèi)容。 (3)構(gòu)建網(wǎng)絡(luò)搜索熱詞的指標體系。根據(jù)指標體系構(gòu)建的依據(jù)和原則,首先篩選出基準熱詞,然后通過熱詞推薦工具獲取所有相關(guān)熱詞,最后依據(jù)熱詞的相關(guān)系數(shù)來確定是否選取。 (4)研究世園會客流量預(yù)測及預(yù)警的相關(guān)模型。本文利用回歸理論構(gòu)建世園會客流量的預(yù)測模型,同時利用灰色災(zāi)變理論構(gòu)建世園會客流量的預(yù)警模型。 (5)以西安世園會為研究對象,通過西安世園會驗證預(yù)測和預(yù)警模型的準確性,然后論述該模型亦可應(yīng)用到青島世園會。 (6)總結(jié)所做的工作,提出本文需要進一步改進的方向和對未來的展望。
[Abstract]:With the popularity of the Internet, the rapid development of the tourism industry, the Internet technology is widely applied to the tourism industry. At present, the Internet as an important platform for the dissemination of information, the relevant personnel of many scenic spots using the Internet to publish some tourist information, the majority of tourists before the trip through the Internet to get travel information. In view of social behavior of the scholars on the Internet the technology that has a certain network search volume and social behavior of Internet hot words, social behavior to guide practice, including tourism behavior. Research for the promotion of Internet behavior, Baidu and Google launched Baidu index and Google two products, related to the query hot words for the majority of scholars web search the amount of convenience.
In this paper, through the use of qualitative, quantitative, empirical research method, proved the relevance between the actual traffic network hot word search volume and World Horticultural Exposition. The network search behavior to build the world park passenger traffic forecasting and early warning model based on the research results based on network behavior, construct the index system of World Horticultural Exposition network hot word search, use Google provides Web searches, using regression analysis, grey theory of traffic forecasting and early warning in World Horticultural Exposition, and through the empirical validation of the model is practical. The main contents of this paper include the following six aspects:
(1) elaborate the background and significance of the research, analyze the research status of web search behavior both at home and abroad, and propose the main contents, research framework, research methods and technology roadmap.
(2) analyze the related theories in this paper, including web search behavior and data processing. First, introduce the functions and application methods of Google trend, and then introduce the grey system theory, including principles, characteristics and main contents.
(3) set up the index system of hot words. According to the basis and principles of index system construction, we first screened out the benchmark hot words, and then got all relevant hot words through the hot word recommendation tool, and finally determined the selection according to the correlation coefficient of the hot words.
(4) to study the relevant models of forecasting and early-warning of the world park's passenger volume. This paper applies regression theory to build the prediction model of the world park's passenger volume, and constructs the early-warning model of the world park's passenger volume based on the grey catastrophe theory.
(5) in Xi'an World Horticultural Exposition as the research object, the accuracy of forecasting and early warning model verification of Xi'an World Horticultural Exposition, and then discusses the model can also be applied to the Qingdao World Horticultural Exposition.
(6) summing up the work done and putting forward the direction for further improvement and prospects for the future.

【學(xué)位授予單位】：青島理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP391.3;F591

【參考文獻】

相關(guān)期刊論文 前10條

1 孫根年;馬麗君;;基于本底線的2008年北京奧運會客流量預(yù)測[J];地理研究;2008年01期

2 朱金亮;李玉平;蔡運龍;;基于灰色預(yù)測模型的河北省生態(tài)足跡動態(tài)分析與預(yù)測[J];干旱區(qū)資源與環(huán)境;2011年02期

3 靜恩英;;調(diào)查問卷設(shè)計的程序及注意問題[J];湖北民族學(xué)院學(xué)報(哲學(xué)社會科學(xué)版);2009年06期

4 劉穎;呂本富;彭賡;;網(wǎng)絡(luò)搜索對股票市場的預(yù)測能力:理論分析與實證檢驗[J];經(jīng)濟管理;2011年01期

5 張淵,陸玉梅,梅強;科技計劃項目績效評估指標體系研究[J];科技管理研究;2005年09期

6 張朝元;陳麗;;基于PCA改進的SOR-LS-SVM旅游流量預(yù)測模型[J];科技通報;2013年03期

7 王小平;孫彩賢;;基于多元回歸模型的2010年上海世博會客流量預(yù)測分析[J];江漢大學(xué)學(xué)報(自然科學(xué)版);2010年02期

8 楊名桂;楊曉霞;;基于灰色預(yù)測模型的重慶市入境旅游客流量預(yù)測[J];西南師范大學(xué)學(xué)報(自然科學(xué)版);2010年03期

9 王世超;嚴艷;;中國三大園藝博覽會的對比分析——暨對西安2011年世園會的相關(guān)建議[J];資源開發(fā)與市場;2010年06期

10 周子健;;基于網(wǎng)絡(luò)搜索量的上海世博會國際影響力研究[J];藝海;2011年05期

相關(guān)博士學(xué)位論文 前1條

1 馬麗君;中國典型城市旅游氣候舒適度及其與客流量相關(guān)性分析[D];陜西師范大學(xué);2012年

，

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