進階神域 的英文怎麼說
中文拼音 [jìnjiēshényù]
進階神域
英文
prestige domain-
423 persons answered the questionnaires and 139 out of them were identified as ecotourists. the result of classification is proved to be effective by prediction validity test, content validity test, theory validity test and convergence validity test. in addition, the ecotourists were classified as hard ecotourists, frequent ecotourists and occasional ecotourists farther according to the times they traveled to nature - based destinations every year and their new ecological paradigm grade which is used to evaluate the visitors attitude to environment. frequent ecotourists and occasional ecotourists both fall category of soft ecotourists, so the " hard - soft " classification system is founded, which will help propel ecotourist studies in china to develop towards the current international mainstream of the field
以北京市百花山自然保護區為例，在總結國外相關研究經驗的基礎上，採用k階最近鄰knn和反向傳播bp前饋型多層神經網路所構成的綜合分類器對百花山遊客中的生態旅遊者進行識別，又根據「每年去相對原始的自然區域的旅遊次數」和環境態度尺度nep得分兩項指標將生態旅遊者進一步細分為嚴格的生態旅遊者經常的生態旅遊者和偶爾的生態旅遊者，其中經常的生態旅遊者和偶爾的生態旅遊者歸為一般的生態旅遊者，從而構建起嚴格的一般的生態旅遊者分類體系。With the development of communication, information and electronic technology and computer network, intelligent transport system ( its ) is paid more and more emphasis, it contains many parts, such as vehicle type recognition and license plate recognition. in this paper, we introduce svm to the field of its, the main work is described as follows : ( 1 ) we summarize the latest research achievements and development of its, present the conceptions of slt and the principles of svm ; ( 2 ) taking the traffic sign as examples and adopting hough transform in the stage of feature extraction, we introduce svm to the problem of shape recognition and compare the experimental results with traditional learning methods. ( 3 ) then we use svm to settle the vehicle type recognition problem, where we utilize the wavelet analysis and mathematical morphology method to extract the figure feature
本文將支持向量機引入智能交通系統領域，主要進行的工作如下： （ 1 ）整理總結了國內外學術界關于統計學習理論方面的研究成果，介紹統計學習理論的基本概念和支持向量機的基本原理； （ 2 ）在形狀識別問題中以交通標志圖像作為實驗對象，利用hough變換進行特徵提取，在識別階段利用支持向量機方法進行分類，並與神經網路等傳統學習方法對比； （ 3 ）將支持向量機應用於車型識別問題中，針對收費站採集的汽車圖像，首先採用小波分析和數學形態學的方法提取其外形特徵，在識別階段利用支持向量機方法進行分類，並與其他傳統學習方法進行了對比； （ 4 ）將支持向量機應用於車牌識別問題中，車牌識別包括車牌定位、車牌字元分割以及字元識別三個步驟，先採用數學形態學方法對車牌區域進行定位，然後採用top - hat變換等方法分割車牌字元，在識別階段採用支持向量機演算法進行字元識別，取得了較為滿意的結果。Applied in license plate segmentation problem, a new segmentation method of automobile license plate based on wavelet transform and neural network is pointed out [ 71 ]. 2 ) phase of image feature extraction : combined with the feature extraction of structural and statistical method, a method of image character feature extraction based on wavelet and moments analysis is presented [ 74j. 3 ) phase of image classificaton [ 73 ] : after investigation on intelligence recognition technology, the paper puts forward basic structure of recognition machine ' s model, and makes a primary research of basic structure and design method, then makes research of the multi - character method
並應用於車牌分割問題，提出基於小波與神經元模式識別的車牌圖像分割方法； 2 ）特徵提取階段：將結構特徵提取方法和統計特徵提取方法的緊密有機結合，提出一種基於小波和矩的車牌圖像字元特徵向量提取方法； 3 ）分類識別階段：對智能識別技術進行研究，提出智能識別機的模型結構，對識別機的基本層次結構和設計方法進行初探；並針對多特徵方法進行一定的研究；本文提出的基於模式識別的圖像處理方法對其他領域的圖像處理具有一定的參考價值。The energy consumption analysis and experiment of the two systems, which are pump - control - motor speed governing system with inverter and hydraulic speed governing system with inlet throttle, are given. software direct compensating motor speed loss of open loop pump - control - motor speed governing system with inverter is studied deeply in theory and experiment. the applications of fuzzy control, single neuron control and genetic algorithm in pump - control - motor speed governing system with inverter are studied, and some useful conclusions are obtained
所進行的主要研究工作如下：對主要參數對變頻泵控馬達調速系統的性能影響進行了時域模擬分析和開環階躍響應實驗研究；對變頻泵控馬達調速系統和進口節流閥控馬達調速系統進行了能耗分析和對比實驗研究；對軟體直接補償開環變頻泵控馬達調速系統的馬達轉速降落進行了理論分析和實驗研究；對變頻泵控馬達調速系統進行了復合補償控制實驗研究；研究了模糊控制、單神經元控制和遺傳演算法在變頻泵控馬達調速系統中的應用，均得到了有益的結論。This paper organizes as follows : chapter 1 mainly introduces the research background, and gives a description of the research content of this paper after discusses the research trend on classification in dataming ; chapter 2 focuses on the theory of cart and gives a algorithm which integrates the tree building phase and pruning phase ; chapter 3 gives a detailed description on rbf and proposes the center selection method based on the statistic information of the training dataset. chapter 4 is the design and realization of the classifier. and chapter 5 summarize the work we i done and analyses the work to do later and obtain the research subject in the future
本論文的組織結構為：第一章為緒論，介紹了研究背景和分類分析研究領域國內外的研究動態，闡述了本文的主要研究內容；第二章詳細敘述了cart分類器的原理，給出了建樹與修剪階段合併的演算法；第三章描述了rbf神經網路分類器，給出了基於樣本統計的網路中心選取方法；第四章講述了cart分類器的設計與實現；第五章對本課題的研究工作進行了總結，分析了今後所要進行的工作以及進一步研究的課題。分享友人