本文選題：新型城鎮(zhèn)化　切入點：PSO-SVM　出處：《安徽建筑大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：本文以新型城鎮(zhèn)化內(nèi)涵及發(fā)展模式為理論基礎(chǔ),以支持向量機及粒子群算法為方法指導(dǎo),結(jié)合定性同定量分析、規(guī)范研究與實證研究,實現(xiàn)對我國新型城鎮(zhèn)化發(fā)展水平的評價分析,并根據(jù)實證研究的結(jié)果將全國河北、山西、內(nèi)蒙古等27個省份劃分為四大區(qū)域進行橫向比較27個省份的新型城鎮(zhèn)化發(fā)展現(xiàn)狀,進而得出推動我國新型城鎮(zhèn)化發(fā)展及加快我國新型城鎮(zhèn)化建設(shè)的對策及建議。第一章首先分析了論文的選題背景和研究的目的與意義,分析了推動新型城鎮(zhèn)化發(fā)展對我國整體發(fā)展的意義之所在,其次根據(jù)時間脈絡(luò)對有關(guān)新型城鎮(zhèn)化內(nèi)涵及發(fā)展模式的國內(nèi)外研究進行綜述,再次介紹了本論題所運用的研究方法以及創(chuàng)新之處,最后以技術(shù)路線圖的形式展現(xiàn)了本文的研究思路。第二章分別闡述并分析了我國新型城鎮(zhèn)化發(fā)展水平評價指標(biāo)方法和我國新型城鎮(zhèn)化發(fā)展水平測度方法的現(xiàn)狀。通過對評價指標(biāo)方法的評述,總結(jié)出我國新型城鎮(zhèn)化相關(guān)指標(biāo)體系的問題,為后續(xù)章節(jié)相關(guān)指標(biāo)體系的構(gòu)建奠定一定現(xiàn)實基礎(chǔ),并分析了當(dāng)前新型城鎮(zhèn)化相關(guān)測度方法的不足,簡略闡述了粒子群算法優(yōu)化支持向量機評價模型的優(yōu)越性。第三章在嚴(yán)格遵循指標(biāo)體系建立基本原則的基礎(chǔ)上,參考現(xiàn)今國內(nèi)學(xué)者對新型城鎮(zhèn)化相關(guān)評價研究的成果,對源自全國河北、山西、內(nèi)蒙古等27個省份2012年度總數(shù)達1600多個指標(biāo)數(shù)據(jù)進行標(biāo)準(zhǔn)化預(yù)處理,并將SPSS18.0應(yīng)用于這些標(biāo)準(zhǔn)化后的數(shù)據(jù),由此輸出顯著性與相關(guān)性矩陣,并根據(jù)該矩陣對初選指標(biāo)進行指標(biāo)篩選,進而構(gòu)建了我國新型城鎮(zhèn)化發(fā)展水平評價的指標(biāo)體系。第四章首先描述了我國新型城鎮(zhèn)化發(fā)展現(xiàn)狀,并分開闡述了支持向量機同粒子群算法的相關(guān)原理并敘述了PSO-SVM的運行流程,意在強調(diào)PSO-SVM方法的科學(xué)性及合理性。其次,基于粒子群算法優(yōu)化支持向量機對我國新型城鎮(zhèn)化發(fā)展水平評價問題進行實證研究。本章根據(jù)第三章所確定的評價方法以及評價指標(biāo)體系,利用河北、山西、內(nèi)蒙古等27個省份的篩選后的指標(biāo)數(shù)據(jù),在Matlab平臺上建立了基于PSO-SVM的我國新型城鎮(zhèn)化發(fā)展水平評價模型,利用相關(guān)程序語言實現(xiàn)運行。程序運行結(jié)果顯示,均方誤差是0.00565827;與綜合評價值曲線的擬合相關(guān)系數(shù)是99.7104%,這說明回歸結(jié)果具有一定科學(xué)性,通過PSO優(yōu)化SVM所得到的最佳懲罰因子及核函數(shù)分別為10.0179和0.0527。最后,本章根據(jù)仿真結(jié)果對我國27個省份的新型城鎮(zhèn)化發(fā)展水平進行了劃區(qū)域評價及結(jié)果分析,并有針對性的提出相應(yīng)的對策及建議,意在為我國27個省份持續(xù)推動新型城鎮(zhèn)化建設(shè)提供一定建設(shè)性的建議。第五章首先對全文的研究進行總結(jié),得出本論題的研究結(jié)論,相關(guān)結(jié)論如下:(1)東部地區(qū)新型城鎮(zhèn)化發(fā)展水平較高,優(yōu)勢較為明顯;(2)中部地區(qū)新型城鎮(zhèn)化發(fā)展水平相對滯后;(3)西部地區(qū)新型城鎮(zhèn)化發(fā)展水平呈現(xiàn)階梯分布。其次,對本論題未來進一步的研究方向從評價指標(biāo)體系及測度方法兩個方面做出了展望。
[Abstract]:In this paper, and the development of new urbanization connotation model as the theoretical basis, based on the support vector machine and particle swarm algorithm as the guidance of methodology, combining qualitative analysis with quantitative analysis, normative research and positive research, analysis and evaluation of the level of development of new towns in China, and according to the empirical research results will be the Hebei, Shanxi, Inner Mongolia the 27 provinces are divided into the current situation of the development of the new urbanization comparing the four regions of 27 provinces, then promote the development of China's new urbanization and the countermeasures and suggestions about accelerating the construction of the new urbanization of our country. The first chapter analyzes the purpose and significance of the background of the research and analysis, to promote the development of the new urbanization of China's overall development significance, secondly according to the time sequence of the relevant research on new urbanization connotation and mode of development at home and abroad are reviewed, introduced again Research methods used in this thesis and innovation, the technology roadmap reflects the idea of this paper. The second chapter describes and analyzes the status quo of China's new urbanization development level evaluation method and method for the development of China's new urbanization level measure. Through the analysis of evaluation index method, summary a relevant index system of the new towns in China, lay a realistic basis for the following chapters to construct relevant index system, and analysis of the current shortage of relevant measurement methods of the new town, explains the advantages of particle swarm optimization support vector machine evaluation model. In the third chapter, based on follow the establishment of index system of basic on the principle of reference to today's domestic scholars research results related to evaluation of the new town of Hebei, from the national, Shanxi, Inner Mongolia and other 27 provinces 201 The year 2 a total of more than 1600 data standardization processing, and the application of SPSS18.0 in the standardized data, the resulting output significantly and correlation matrix, and according to the matrix of the primary index of index selection, and then constructed the evaluation index system of the development level of the new urbanization in China. The fourth chapter describes the current development of new urbanization in China, and expounds the principle of separate support vector machine with particle swarm algorithm and describes the operation process of PSO-SVM, the PSO-SVM method is intended to emphasize the scientificity and rationality. Secondly, the particle swarm optimization support vector machine development level evaluation of new towns in China, empirical research based on this chapter. The third chapter according to the evaluation method and evaluation index system, the use of Hebei, Shanxi, Inner Mongolia and other screening index data of 27 provinces in the Matl AB platform is established on the level of development of China's new urbanization evaluation model based on PSO-SVM, realize the operation of using programming language. The program running results show that the mean square error is 0.00565827; and the comprehensive evaluation value curve fitting correlation coefficient is 99.7104%, which shows that the regression result is scientific, through optimal penalty factor and kernel PSO function optimization of SVM are 10.0179 and 0.0527. respectively at the end of this chapter, according to the simulation results of new towns in 27 provinces of our country the development level of the designated area evaluation and result analysis, and put forward the corresponding countermeasures and suggestions, in order to provide some constructive for the 27 provinces in our country continuously promote the construction of new urbanization. The fifth chapter summarizes the research conclusion, the research of this thesis, the related conclusions are as follows: (1) the new urbanization development of the eastern region The level is higher, the more obvious advantages; (2) new towns in the central region development is lagging behind the level; (3) the new urbanization of western region development shows a ladder distribution. Secondly, the further research direction of the topic of the future from two aspects of the evaluation index system and measure method is prospected.

【學(xué)位授予單位】：安徽建筑大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：F299.21;F224

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