本文關(guān)鍵詞：基于ARIMA與SVM組合模型的國(guó)內(nèi)旅游市場(chǎng)預(yù)測(cè)研究　出處：《東華理工大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 國(guó)內(nèi)旅游市場(chǎng) 灰色關(guān)聯(lián)分析 ARIMA SVM 組合模型

【摘要】：改革開放以來(lái),隨著中國(guó)經(jīng)濟(jì)與國(guó)民收入的增長(zhǎng),旅游業(yè)這項(xiàng)活動(dòng)日益大眾化,并在政治、經(jīng)濟(jì)、社會(huì)、文化、生態(tài)等領(lǐng)域顯示出巨大活力。目前,中國(guó)國(guó)內(nèi)旅游已成為世界上增速最快、數(shù)量最多、潛力最大的旅游市場(chǎng),其發(fā)展規(guī)模已超過(guò)入境旅游和出境旅游,在經(jīng)濟(jì)發(fā)展中占據(jù)極其重要的地位。因此,如何在未來(lái)中把握和預(yù)測(cè)國(guó)內(nèi)旅游市場(chǎng)發(fā)展的趨勢(shì),為旅游企業(yè)和管理者做出正確決策就成為政府必須要解決的現(xiàn)實(shí)問(wèn)題。本文首先對(duì)國(guó)內(nèi)旅游市場(chǎng)的背景進(jìn)行了探討,論述了研究的內(nèi)容、方法和意義。接著對(duì)1995-2015年影響國(guó)內(nèi)旅游市場(chǎng)因素的數(shù)據(jù)進(jìn)行了灰色關(guān)聯(lián)度分析,通過(guò)平均絕對(duì)百分誤差(MAPE)的大小來(lái)判斷各個(gè)模型對(duì)國(guó)內(nèi)旅游人數(shù)預(yù)測(cè)的精度。在此基礎(chǔ)上,對(duì)交通和城市居民人均可支配收入進(jìn)行預(yù)測(cè)并利用預(yù)測(cè)數(shù)據(jù)對(duì)國(guó)內(nèi)旅游人數(shù)進(jìn)行預(yù)測(cè)。最后根據(jù)未來(lái)國(guó)內(nèi)旅游人數(shù)的持續(xù)增長(zhǎng)所帶來(lái)的問(wèn)題(交通擁擠、旅游景區(qū)安全、旅游服務(wù)質(zhì)量下降和市場(chǎng)秩序混亂)提出一些建議和對(duì)策。主要研究結(jié)論如下:(1)運(yùn)用灰色關(guān)聯(lián)分析法對(duì)影響國(guó)內(nèi)旅游市場(chǎng)的因素(交通(公路鐵路總里程)、旅游產(chǎn)品價(jià)格(CPI)、旅游環(huán)境(國(guó)內(nèi)旅游收入)和城市居民人均可支配收入)進(jìn)行關(guān)聯(lián)度分析,結(jié)果證明交通對(duì)其影響最大,其次是城市居民人均可支配收入。(2)運(yùn)用差分自回歸移動(dòng)平均(ARIMA)、支持向量機(jī)(單因素SVM和多因素SVM)以及組合模型對(duì)國(guó)內(nèi)旅游人數(shù)進(jìn)行預(yù)測(cè)比較,并考慮到國(guó)內(nèi)旅游人數(shù)時(shí)間序列數(shù)據(jù)的線性與非線性的特征,結(jié)果證明組合模型預(yù)測(cè)的精確度更高,泛化能力更強(qiáng)。(3)全國(guó)國(guó)內(nèi)旅游人數(shù)與交通(公路鐵路總里程)、旅游產(chǎn)品價(jià)格(CPI)、旅游環(huán)境(國(guó)內(nèi)旅游收入)和城市居民人均可支配收入存在高度正相關(guān),特別是在經(jīng)濟(jì)發(fā)展的初期,經(jīng)濟(jì)發(fā)展對(duì)國(guó)內(nèi)旅游人數(shù)的依賴性較強(qiáng),并運(yùn)用泛化能力更強(qiáng)、精確度更高的組合模型對(duì)影響國(guó)內(nèi)旅游人數(shù)最大的兩個(gè)因素(交通和可支配收入)預(yù)測(cè),然后通過(guò)三次多項(xiàng)式回歸對(duì)其進(jìn)行預(yù)測(cè),結(jié)果發(fā)現(xiàn),交通對(duì)國(guó)內(nèi)旅游人數(shù)的預(yù)測(cè)結(jié)果更為可靠。(4)全國(guó)國(guó)內(nèi)旅游人數(shù)在1995-2004年增加比較平穩(wěn),2005-2015年旅游人數(shù)增加趨勢(shì)加速。從預(yù)測(cè)結(jié)果來(lái)看,未來(lái)十年國(guó)內(nèi)旅游人數(shù)會(huì)趨增,旅游市場(chǎng)規(guī)模會(huì)進(jìn)一步擴(kuò)大,人均出游率達(dá)9.6次,旅游消費(fèi)將大大提高。這和國(guó)家對(duì)旅游產(chǎn)業(yè)的大力支持及經(jīng)濟(jì)結(jié)構(gòu)的調(diào)整和轉(zhuǎn)型是相吻合的。
[Abstract]:Since the reform and opening up, with the growth of China's economy and national income, tourism has become increasingly popular, and has shown great vitality in political, economic, social, cultural, ecological and other fields. China's domestic tourism has become the world's fastest growing, the largest number, the largest potential tourism market, its development scale has exceeded the inbound tourism and outbound tourism, occupies an extremely important position in the economic development. How to grasp and predict the development trend of domestic tourism market in the future. To make the correct decision for tourism enterprises and managers becomes a realistic problem that must be solved by the government. Firstly, this paper discusses the background of domestic tourism market and discusses the content of the research. Methods and significance. Then the data of influencing factors of domestic tourism market from 1995 to 2015 were analyzed by grey correlation degree. Through the average absolute percent error of the size of MAPE to judge the accuracy of each model for the domestic tourist population prediction. On this basis. Forecast the per capita disposable income of traffic and urban residents and forecast the number of domestic tourism by using the forecast data. Finally, according to the problems caused by the sustained growth of the number of domestic tourism (traffic congestion) in the future. Scenic spots are safe. Some suggestions and countermeasures are put forward for the decline of tourism service quality and confusion of market order. The main conclusions are as follows: 1) the grey relational analysis is used to analyze the factors (traffic) affecting the domestic tourism market. Total road and rail mileage). The correlation analysis of tourism product price CPI, tourism environment (domestic tourism income) and per capita disposable income of urban residents shows that traffic has the greatest impact on it. The second is the per capita disposable income of urban residents. 2) using differential autoregressive moving average (ARIMA). Support vector machine (single factor SVM and multivariate SVM) and combination model are used to predict and compare the number of domestic tourists, taking into account the linear and nonlinear characteristics of the time series data of domestic tourist population. The results show that the forecasting accuracy of the combined model is higher and the generalization ability is stronger. 3) the number of domestic tourism and transportation (total mileage of road and railway, the price of tourism product is higher than CPI). Tourism environment (domestic tourism income) and per capita disposable income of urban residents have a high positive correlation, especially in the early stage of economic development, economic development has a strong dependence on the number of domestic tourism. And using the combination model with stronger generalization ability and higher accuracy to predict the two factors (traffic and disposable income) that affect the number of domestic tourism, and then predict it by cubic polynomial regression. The result shows that the forecast result of the traffic to the domestic tourist population is more reliable. 4) the increase of the domestic tourist population in the whole country from 1995 to 2004 is relatively stable. From the forecast results, the number of domestic tourism will increase in the next decade, the scale of the tourism market will further expand, the per capita travel rate reaches 9.6. Tourism consumption will be greatly increased. This is consistent with the state's strong support for the tourism industry and the adjustment and transformation of the economic structure.
【學(xué)位授予單位】：東華理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F592.6

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