本文關(guān)鍵詞：基于CPM-RBF模型的區(qū)域土地生態(tài)安全預(yù)警研究　出處：《中國(guó)地質(zhì)大學(xué)(北京)》2015年碩士論文　論文類(lèi)型：學(xué)位論文

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【摘要】：健康的土地生態(tài)系統(tǒng)是維系區(qū)域生態(tài)安全的重要因素,開(kāi)展區(qū)域土地生態(tài)安全預(yù)警研究,分析土地生態(tài)安全警情演變狀況,是新形勢(shì)下建設(shè)生態(tài)文明建設(shè)現(xiàn)實(shí)需要,也是進(jìn)一步完善土地生態(tài)安全研究的理論需求。為此,本文以山西省臨汾市堯都區(qū)為研究區(qū)域,以土地生態(tài)安全相關(guān)理論為理論指導(dǎo),采用突變級(jí)數(shù)法和徑向基函數(shù)神經(jīng)網(wǎng)絡(luò)模型開(kāi)展了區(qū)域土地生態(tài)安全預(yù)警研究。本文主要開(kāi)展了以下幾個(gè)方面內(nèi)容的研究:(1)對(duì)國(guó)內(nèi)外相關(guān)研究進(jìn)行綜述性介紹與回顧,探討不同研究?jī)?nèi)容與技術(shù)方法的側(cè)重點(diǎn),明晰本文研究的起點(diǎn);(2)分析研究區(qū)土地生態(tài)安全現(xiàn)狀,指出區(qū)域土地生態(tài)安全面臨的形勢(shì);(3)在分析“壓力—狀態(tài)—響應(yīng)”(PSR)框架模型和“自然—經(jīng)濟(jì)—社會(huì)”(NES)框架模型各自特點(diǎn)的基礎(chǔ)上,構(gòu)建基于PSR-NES框架模型的區(qū)域土地生態(tài)安全預(yù)警指標(biāo)體系;(4)引入常見(jiàn)突變模型創(chuàng)建了研究區(qū)土地生態(tài)安全警情分析模型,運(yùn)用突變級(jí)數(shù)法對(duì)土地生態(tài)安全警情變化進(jìn)行分析;(5)在Matlab中直接調(diào)用徑向基函數(shù),運(yùn)用RBF神經(jīng)網(wǎng)絡(luò)對(duì)區(qū)域土地生態(tài)安全警情演變趨勢(shì)進(jìn)行預(yù)測(cè)。通過(guò)對(duì)以上內(nèi)容進(jìn)行研究,得出以下結(jié)論:(1)經(jīng)濟(jì)和社會(huì)因素是造成區(qū)域土地生態(tài)安全動(dòng)態(tài)演變的主要因素;(2)PSR-NES框架模型的區(qū)域土地生態(tài)安全預(yù)警指標(biāo)體系較為全面且有針對(duì)性,有助于判斷區(qū)域土地生態(tài)安全真實(shí)狀態(tài)以及發(fā)現(xiàn)土地生態(tài)安全演變過(guò)程中存在的問(wèn)題;(3)突變級(jí)數(shù)法含義較為明晰,可操作性強(qiáng),減少預(yù)警過(guò)程中人為主觀性影響,應(yīng)用于土地生態(tài)安全預(yù)警研究是一個(gè)較好的嘗試;(4)RBF神經(jīng)網(wǎng)絡(luò)具有訓(xùn)練速度快、能收斂到全局最優(yōu)點(diǎn)等特點(diǎn),能夠不斷的學(xué)習(xí)確定徑向基函數(shù)的最優(yōu)參數(shù),提高警情預(yù)測(cè)精度;(5)構(gòu)建了土地生態(tài)安全預(yù)警的CPM-RBF模型,整個(gè)過(guò)程邏輯性強(qiáng)、思路清晰。本文的創(chuàng)新點(diǎn)是將突變理論運(yùn)用到土地生態(tài)安全預(yù)警研究中,運(yùn)用突變級(jí)數(shù)法對(duì)土地生態(tài)安全警情變化進(jìn)行了分析,運(yùn)用RBF神經(jīng)網(wǎng)絡(luò)對(duì)警情演變趨勢(shì)進(jìn)行預(yù)測(cè),但是該研究還存在一些有待改進(jìn)之處,預(yù)警指標(biāo)體系有待進(jìn)一步優(yōu)化,警情等級(jí)劃分標(biāo)準(zhǔn)需要進(jìn)一步探討,這些都有待后續(xù)研究進(jìn)一步完善,本文僅僅為區(qū)域土地生態(tài)安全預(yù)警研究在方法上提供了一種新的思路。
[Abstract]:Healthy land ecosystem is an important factor to maintain regional ecological security. It is the realistic need of constructing ecological civilization under the new situation, and is also the theoretical demand to further improve the study of land ecological security. Therefore, this paper takes Yaodu District, Linfen City, Shanxi Province as the research area. It is guided by the theory of land ecological security. Using the catastrophe series method and the radial basis function neural network model, the early warning study of regional land ecological security is carried out. The related research at home and abroad is reviewed and reviewed. The emphasis of different research contents and technical methods is discussed, and the starting point of this study is clarified. 2) analyzing the present situation of land ecological security in the research area and pointing out the situation that the regional land ecological security is facing; 3) based on the analysis of the characteristics of the "pressure-state-response" (PSR) framework model and the "natural-economic-social" (NES) framework model. Constructing the early warning index system of regional land ecological security based on PSR-NES framework model; 4) introducing the common catastrophe model to establish the analysis model of the land ecological security in the study area, and analyzing the change of the land ecological security alarm by using the catastrophe series method. 5) the radial basis function is called directly in Matlab, and RBF neural network is used to predict the evolution trend of regional land ecological security. The following conclusions are drawn: (1) Economic and social factors are the main factors that cause the dynamic evolution of regional land ecological security; The early warning index system of regional land ecological security based on PSR-NES framework model is comprehensive and targeted. It is helpful to judge the real state of regional land ecological security and to find out the problems existing in the evolution of land ecological security. (3) the sudden change series method has a clear meaning and strong maneuverability, so it is a good attempt to reduce the human subjectivity in the early warning process and to apply it to the study of land ecological security early warning. The RBF neural network has the characteristics of fast training speed, converging to the global optimum and so on. It can continuously learn to determine the optimal parameters of the radial basis function and improve the prediction accuracy of the warning situation. 5) the CPM-RBF model of land ecological security warning is constructed, the whole process is logical and the idea is clear. The innovation of this paper is to apply the catastrophe theory to the study of land ecological security early warning. The sudden change series method is used to analyze the changes of land ecological security alarm situation, and the RBF neural network is used to predict the trend of police situation evolution. However, there are still some problems to be improved in this study. The early warning index system needs to be further optimized, and the criteria for classification of police situation grades need to be further explored, all of which need to be further improved in the follow-up study. This paper only provides a new way for the study of early warning of regional land ecological security.
【學(xué)位授予單位】：中國(guó)地質(zhì)大學(xué)(北京)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：F301;X171.1

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