本文選題：經(jīng)濟(jì)預(yù)測(cè)　切入點(diǎn)：指標(biāo)體系　出處：《重慶大學(xué)》2014年碩士論文

【摘要】：經(jīng)濟(jì)的增長(zhǎng)能夠促進(jìn)城市各方面的發(fā)展，城市發(fā)展起來了又可以帶動(dòng)經(jīng)濟(jì)的發(fā)展。因此，研究城市的經(jīng)濟(jì)發(fā)展?fàn)顩r便有了舉足輕重的意義。隨著生活質(zhì)量的提高，經(jīng)濟(jì)的大發(fā)展，人們開始關(guān)注起經(jīng)濟(jì)的走勢(shì)，越來越多的學(xué)者投入到經(jīng)濟(jì)狀況及其未來發(fā)展的研究熱潮中去。然而經(jīng)濟(jì)系統(tǒng)是一個(gè)復(fù)雜且多變的系統(tǒng)，要探索清楚它的本質(zhì)勢(shì)必具有一定的難度。 用于經(jīng)濟(jì)預(yù)測(cè)的變量通常較多，過多的變量就容易產(chǎn)生多重共線性的問題，為了消除該影響，出現(xiàn)了提取成分的思想。偏最小二乘（PLS）集合了相關(guān)分析、成分提取、回歸擬合等眾多優(yōu)勢(shì)，成為了現(xiàn)今研究的熱點(diǎn)。近年來，機(jī)器學(xué)習(xí)開始活躍起來，新興的支持向量機(jī)（SVM）從最初的解決分類問題擴(kuò)展到回歸擬合上去，展現(xiàn)出了其獨(dú)特的優(yōu)勢(shì)，受到眾人的追捧。 本文首先介紹了城市經(jīng)濟(jì)預(yù)測(cè)的研究背景及相關(guān)知識(shí)。然后，本文開始介紹PLS和SVM的相關(guān)理論，為后文的研究作好了準(zhǔn)備。之后開始進(jìn)行實(shí)證分析。本文根據(jù)1997-2012年的相關(guān)數(shù)據(jù)建立了PLS-SVM模型，并預(yù)測(cè)出2013年的GDP值，根據(jù)預(yù)測(cè)誤差來看，擬合效果比較理想。接著，本文又建立了與本模型思想相似的PCA-SVM模型和直接的SVM模型，用于與本模型進(jìn)行比較分析。最終，，本文得出了PLS-SVM模型的擬合效果優(yōu)于另兩種模型的結(jié)論。 本文具備良好的實(shí)用性和適用性，利于擴(kuò)大推廣。
[Abstract]:Economic growth can promote the development of all aspects of the city, urban development can also lead to economic development.Therefore, the study of the economic development of the city has a pivotal significance.With the improvement of quality of life and the great development of economy, people begin to pay attention to the trend of economy, and more and more scholars are engaged in the upsurge of research on economic situation and its future development.However, the economic system is a complex and changeable system, it must be difficult to explore its essence.There are usually many variables used in economic prediction, and too many variables are easy to produce multiple collinear problems. In order to eliminate this effect, the idea of extracting components has emerged.Partial least squares (PLS), which has many advantages, such as correlation analysis, component extraction, regression fitting and so on, has become a hot research topic.In recent years, machine learning has become active, and the new support vector machine (SVM) has expanded from the original classification problem to regression fitting, showing its unique advantages, which has been sought after by many people.This paper first introduces the research background and related knowledge of urban economic forecasting.Then, this paper begins to introduce the related theories of PLS and SVM, and prepares for the later research.Then the empirical analysis began.In this paper, the PLS-SVM model is established based on the relevant data from 1997-2012, and the GDP value of 2013 is predicted. According to the prediction error, the fitting effect is satisfactory.Then, the PCA-SVM model and the direct SVM model, which are similar to this model, are established, which are used to compare and analyze the model.Finally, this paper draws the conclusion that the fitting effect of PLS-SVM model is better than that of other two models.This article has the good practicability and the applicability, is advantageous to expand popularizes.
【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：F224;F127

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