神學論集 的英文怎麼說

中文拼音 [shénxuélúnjí]
神學論集 英文
sentences
  • 神 : Ⅰ名詞1 （神靈） god; deity; divinity 2 （精神; 精力） spirit; mind 3 （神氣; 神情） expression; l...
  • 學 : Ⅰ動詞1 （學習） study; learn 2 （模仿） imitate; mimic Ⅱ名詞1 （學問） learning; knowledge 2 （學...
  • 論 : 論名詞（記錄孔子及其門徒的言行的「論語」） the analects of confucius
  • 集 : gatherassemblecollect
  • 神學 : theology神學家 theologian; 神學派 theology; 神學學者 doctor; 神學院 seminary; yeshival
  1. Because color isochromatic fringes appear in the stress model based on a plane polariscope in white light, we studied the problems systematically by a digital camera as image inputting device, digital image processing technique and bp artificial neural network. based on the work that has been reported before, a technique named five - step color phase shifting technique ( fcpst ) to acquire single isoclinics is presented

    根據白光入射時應力模型在偏振儀光學系統中的等色線條紋是彩色的特點，本論文採用彩色數碼相機作為數據採集與輸入設備，結合彩色信息圖像處理和bp神經網路等新技術，對上述兩個難題進行了系統的研究，獲得以下成果：在綜合前人工作的基礎上，提出獲得全場單純的等傾角相圖的五步彩色相移法。
  2. The disquisition includes choice of algorithm, accomplish of algorithm, collection of learning sample, parameter of net, shortcoming of bp algorithm, extraction and reduction form line etc. referring to shortcoming of traditional bp algorithm, a modified learning factor with adaptation is introduced. because of every different font has robust, the way based chain coded and knaggy feature is used. a bizarre sample feature database is constructed for speeding up modified bp learning and classification

    本文對人工神經網路理論進行了研究，探討了網路形式及演算法的選擇、演算法的實現、學習樣本的收集、網路參數選擇、 bp演算法缺陷、表格線提取、還原、生成及字元識別、還原生成等問題，並針對bp演算法的缺陷提出了和實現了改進型bp演算法，使網路學習效率提高，對不同人的不同字型字體有較強的魯棒性，採用了基於鏈碼特徵和凹凸分佈特徵的方法來抽取字元特徵。
  3. Mainly in a way of myth and archetypal criticism, combined with jung ' s theory of archetypes and the collective unconscious, this article tries to concretely analyze the theme of lord of the flies so as to exhibit another facet of the novel

    摘要以神話原型批評理論為指導，結合分析心理學創始人榮格的原型說與集體無意識理論，從新的角度對《蠅王》進行剖析和探討。
  4. On the basis of introducing the theory of fuzzy control ( fc ) and neural network ( nn ) as a whole, this paper presented a new mixed control method, which was called as neural network - fuzzy control. ( nn - fc ). the nn - fc method combined the strong self - study ability of neural network and powerful experience - expressing ability of fuzzy control to meet the need of real - time control

    在系統地介紹智能控制理論中的模糊控制和神經網路控制理論之後，引入了模糊控制和神經網路控制相結合的產物? ?神經模糊控制，將模糊邏輯推理的強大結構性知識表達能力與神經網路的強大自學習能力集於一體，彌補了模糊控制需要系統先驗知識且缺乏自學習功能的不足。
  5. In this paper, we studied the deterministic mechanism of isi with the unstable period orbit ( upo ) ; we tested many isi data from different model with the method of approximate entropy ( apen ) to study the method which is used in testing the degree of complicacy of isi and we built up a system including hardware and software for our lab to view and record action potential, firing frequency and isi in real time. results 1. spontaneous firing patterns were observed from neurons of supraoptic nucleus ( son ) in hypothalamus with the method of patch clamp

    本研究通過對大鼠視上核神經元自發放電的非穩定周期軌道的計算，討論了isi的確定性問題；利用近似熵的方法對多種神經放電的isi資料進行了復雜度的測量，討論了這種方法在isi的復雜度測量第四軍醫大學碩士論文中的應用；另外，還開發出一套記錄原始放電和isi的程序，解決了採集isi的問題。
  6. To verify the effectiveness of the proposed hybrid fnn, this thesis addressed the estimation problem for the frozen point of light cyclic oil in a fluidized catalytic cracking unit ( fccu ) in a refinery. based on the sample data collected from the industrial unit, we built a soft sensor model by using an above hybrid fnn

    最後，針對某煉油廠催化裂化裝置主分餾塔輕柴油凝固點的軟測量估計問題，本文基於工業現場所採集的樣本數據，建立了混合結構神經網路模型，並討論該模型的在線自學習問題，同時與多層前向bp網路、徑向基函數rbf網路模型進行了比較。
  7. It possesses not only the self - learning ability and adaptability, but also the function of self - adjusting factors. based on fuzzy set, neural network theory, the fuzzy control model and fuzzy neural network control model of multi variable system are presented. based on the automatic core - welding line of shop floor control system in yangzhou radiator plant computer integrated manufacturing system ( ys - cims / sfcs ), the fuzzy logic theory was applied to the controlling device and established the main heating room fuzzy temperature controller and finally was put into practical use

    本文採用了基於神經網路技術的智能pid控制策略，設計了一類具有自學習和自調整比例因子功能的神經元網路自適應pid控制器的結構及演算法；為解決結構不確定性的復雜多變量系統的控制，基於模糊集及模糊系統、神經網路理論，建立了多變量系統的模糊控制模型及模糊神經網路控制模型；針對揚州水箱廠計算機集成製造系統車間管理與控制系統（ ys - cims sfcs ）中的實際工程問題，設計和開發了散熱器芯子烘焊自動線主烘腔溫度模糊控制器，解決了生產中長期存在的老大難問題，提高了產品質量，降低了單產能耗。
  8. Then, the thesis designs a program model of mechanical fault diagnosis neural network learning and diagnosis, and uses turbo c2. 0 to achieve the total course of fault diagonisis on the gearbox in j ? 0 tractor based on ann theory

    再次，本文設計了機械故障診斷神經網路學習和診斷程序模塊，並利用turboc2 . 0編寫了程序，實現了基於人工神經網路理論的集材- 50拖拉機變速箱故障診斷的全過程。
  9. Based on polymerization reaction of the nylon - 6 rubberized cord fabric production of distributed control system in yangzhou organic chemical plant computer integrated manufacturing system ( yh - cims / dcs ), the multiple stepwise regression method was used to build the statistic mathematical models of the molecule weight and the monomer quantum of casting slice belt. then the optimization model of polymerization reaction was presented, which was solved by using simulation annealing algorithm to obtain the best techniques parameters. the improved hybrid genetic algorithm and back propagation algorithm are combined to train neural network, brought out the neural network prediction model of casting slice belt ' s average molecule weight to guide the technologist on - line

    提出了流程工業生產過程操作優化策略和應用實施方法，包括生產過程離線優化策略、非線性問題求解策略、在線優化模型及學習策略；結合揚州有機化工廠計算機集成製造系統集散控制系統（ yh - cims dcs ）的實施，針對錦綸? 6浸膠南京理工大學博士學位論文摘要簾于布生產中己內酚胺聚合反應過程優化控制這一工程實際問題，採用統計建模方法，建立了聚合反應過程的優化模型；為求解所得的優化模型，提出了種改進的有約束條件下的模擬退火演算法，該演算法能避免陷於局部最優解，有效地提高了所求解的全局性和可靠性：提出了基於改進的ga演算法和sp演算法相結合的混合學習演算法，建立了基於神經網路的聚合反應過程生產目標在線預測模型，該演算法和模型滿足了生產中的實時性和實用性要求。
  10. Viewed from this angle, we find that in the theory of thomas aquinas, a representative figure of medieval philosophy, belief and reason are two interrelated and interpenetrated constituent elements, which are connected with each other intrinsically and necessarily, rather than two independent systems that were mixed together occasionally and unnecessarily

    從這種角度看問題，我們發現，在中世紀哲學的集大成者多瑪斯?阿奎那的思想體系中，信仰與理性並不是兩種截然不同的思維方式，神學與哲學也不是兩個被無原則地摻和在一起的理論體系，而是兩個相互滲透和相互作用的、有著必然的內在聯系的構成要素。
  11. Their learning and training rules have been analyzed profoundly and their abilities to approximate arbitrary nonlinear function have been testified and compared by the simulation. a new rbf neural network has been presented which uses a raised - cosine function as activation transfer function. it provides a wider generalization in comparison with gaussian rbf neural networks by simulation as well as strong approximation ability, fast convergence, a rule to select the parameters of the networks

    本文詳細研究了兩種典型的前向神經網路（ bp網路和rbf網路）的學習和訓練演算法，提出了一種新穎的基於緊支集餘弦函數的徑向基神經網路，其克服了常用的高斯型rbf神經網路雖具有緊支集但各基函數非正交的不足，其收斂速度快、網路參數選取有理論依據且相比于高斯型rbf神經網路具有更強的泛化能力，模擬驗證了其有效性。
  12. Firstly, influence factors of generalization of neural network are presented in this thesis, in order to improve neural network ’ s generalization ability and dynamic knowledge acquirement adaptive ability, a structure auto - adaptive neural network new model based on genetic algorithm is proposed to optimize structure parameter of nn including hidden layer nodes, training epochs, initial weights, and so on ; secondly, through establishing integrating neural network and introducing data fusion technique, the integrality and precision of acquired knowledge is greatly improved. then aiming at the incompleteness and uncertainty problem consisting in the process of knowledge acquirement, knowledge acquirement method based on rough sets is explored to fulfill the rule extraction for intelligent diagnosis expert system, by completing missing value data and eliminating unnecessary attributes, discretization of continuous attribute, reducing redundancy, extracting rules in this thesis. finally, rough sets theory and neural network are combined to form rnn ( rough neural network ) model for acquiring knowledge, in which rough sets theory is employed to carry out some preprocessing and neural network is acted as one role of dynamic knowledge acquirement, and rnn can improve the speed and quality of knowledge acquirement greatly

    本文首先討論了影響神經網路的泛化能力的因素，提出了一種新的結構自適應神經網路學習演算法，在新方法中，採用了遺傳演算法對神經網路的結構參數（隱層節點數、訓練精度、初始權值）進行優化，大大提高了神經網路的泛化能力和知識動態獲取自適應能力;其次，構造集成神經網路，引入數據融合演算法，實現了基於集成神經網路的融合診斷，有效地提高了知識獲取的全面性、完善性及精度;然後，針對知識獲取過程中所存在的不確定性、不完備性等問題，探討了運用粗糙集理論的知識獲取方法，通過缺損數據補齊、連續數據的離散、沖突消除、冗餘信息約簡、知識規則抽取等一系列的演算法實現了智能診斷的知識規則獲取;最後，將粗糙集理論與神經網路相結合，研究了粗糙集-神經網路的知識獲取方法。
  13. Aiming at crack problems in important hydraulic concrete structures, the cause, evolution rule and abnormality diagnosis of the crack are studied in this dissertation by using advanced theories and mathematics and mechanics, such as rough set theory, data mining, neural network, wavelet analysis, chaos theory, and so on, combining with prototype observation data. the main contents are as follows. ( 1 ) mining of cause of crack is proposed by using logic diagnosis, rough set theory, and data mining technique

    本文針對重大水工混凝土結構運行期的裂縫問題，應用粗集理論、數據挖掘、神經網路、小波分析、混沌理論、突變理論等前沿數學方法及斷裂力學等力學方法，以及數值模擬等數值模擬方法和邏輯診斷方法，結合實測資料，對運行期裂縫的成因、演變規律以及轉異診斷等方面進行了系統的研究。
  14. 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。
  15. Based on analyzing the relationship between linear separability and a connected set in boolean space, the particular effect of a restraining neuron in extraction of rules from a bnn is discussed, and that effect is explained through a example called a mis problem in boolean space. in this paper, a pattern match learning algorithm of bnns is proposed. when a bnn has been trained by the algorithm, all the binary neurons of hidden layer belong to one or more ls series, if the logical meanings of those ls series are clear, the knowledge in the bnn can be dug out

    另一個研究成果是在分析線性可分和樣本連通性關系的基礎上，以mis問題為例，討論了抑制神經元在二進神經網路規則提取中的獨特作用，提出了二進神經網路的模式匹配學習演算法，採用這種演算法對布爾空間的樣本集合進行學習，得到的二進神經網路隱層神經元都歸屬於一類或幾類線性可分結構系，只要這幾類線性可分結構系的邏輯意義是清晰的，就可以分析整個學習結果的知識內涵。
  16. Exploration of the convergence of theoretical work and experimental data on neuronal computations that highlight the feedback requirement for the systematic operation of the nervous system

    集中探討了神經計算科學的理論工作和實驗數據，特別討論了神經系統進行系統性運作時反饋的必要性。
  17. In this paper, overall design philosophy and measure while diagonose the prefabricated substation using ann theory are defined, including the definition of fuzzy expression method for fault symptoms, the definition of typical fault collection and typical fault sign collection, the definition of the format of the learning sample and test sample, and the definition of fault diagnosis model formed in coordination by multi ann whose diagnosis principle are also described. a practical software using visual c + + 6. 0 and access2000 as developing instrument are developed on the basis of diagnosis principle put forward by this paper

    本文確定了應用神經網路理論對箱式變電站進行故障診斷的總體設計思想和步驟：確定了監測數據的預處理模糊化方法；建立了箱式變電站典型故障集和典型故障徵兆集；確定了學習樣本的格式，完成了學習樣本的生成；確定了神經網路結構和參數，並對學習樣本應用本文的學習演算法進行了學習訓練，使誤差控制在給定范圍內；以集散監測診斷系統的思想，提出了由多個神經網路協同構成的多神經網路故障診斷模型，並論述了其診斷原理。
  18. ( 4 ) considering such actual difficulties as lacking of engineering data and discrepancy in managing level, four methods for damage assessment are proposed in the thesis based on expert knowledge, which are weighted average method, fuzzy comprehensive evaluation method, generalized quantification method and set pair analysis method to make useful supplements to the neural network method. disadvantageous effects, caused by dissimilarity of subjective factors such as every abstract expert ' s knowledge, level, discernment and emphasis on problem, are eliminated to some extent in each method. furthermore, there are not any complicate mathematic or mechanical calculations, and conclusion can be easily got only by some simple reasoning and comparing from experience

    （ 4 ）考慮到工程資料少、管理水平不一的實際困難，建議了基於專家知識的加權平均法、模糊綜合評判法、模糊廣義量化法和集對論方法等四種損傷評估方法，作為橋梁損傷神經網路評估方法的有益補充，這些方法均能從一定程度上消除由於專家個人偏好、知識層次不同等造成的差異，且一般不涉及復雜的數學或力學計算，只需根據經驗進行一些簡單推理和比較就能得到結果。
  19. The important research is about the theory and methods of the cluster analysis in view of statistical theory, the theory and methods of fuzzy cluster analysis, the fkn " s structure and the fkn ' s study algorithm ( fkn, fuzzy kohonen network ) - the organic fusion of the fuzzy c - means algorithm and self - organized feature map neural network. the paper proposes the ifkn ( improved fkn ) on the basis of the hard classification idea and the soft classification idea, then carries on the cluster analysis of the artificial synthetic control chart time series through matlab program and tt ? cluster result matches the cluster result of the famous dataengine " s software of the intellectual data analysis and data mining from german mit company. finally, the paper discusses the applying of the cluster analysis to the control process, which can be widely applied to the pattern recognition of the parameter " s changing trend during the control process and the image partition processing, and utilizes the ifkn to recognize the thermotechnical parameter " s changing trend based on the engineering of clinker sintering rotary kiln automatic control system of guizhou " s aluminium factory, through which good effect is obtained

    數據挖掘技術在商業領域中已廣泛使用，然而在工業過程式控制制中的應用卻極少，本文正是在這種背景下，對數據挖掘中的聚類分析方法及其在工業過程式控制制中的應用研究作了償試，重點研究了基於統計理論的聚類分析理論和方法，模糊聚類分析理論和方法及模糊kohonen網路（ fkn ）的結構與學習演算法，即模糊c ? ?均值演算法與自組織特徵映射神經網路（ kohonen網路）的有機融合，並根據硬分類思想及軟分類思想提出了改進的模糊kohonen網路（ ifkn ） ，通過matlab編程對人工合成控制時序圖數據集進行聚類分析，其聚類效果與當今廣泛使用的數掘挖掘軟體平臺，德國mit公司著名的dataengine智能數據分析和數掘挖掘軟體的聚類效果相當，最後，論述了聚類分析在控制中的應用，它可以用於過程式控制制中的參數變化趨勢的模式識別及圖象分割處理等具體應用中，並以貴州鋁廠熟料燒結回轉窯自動控制系統為工程背景，利用ifkn識別其熱工參量變化趨勢，取得了較理想的效果。
  20. Sc has potential to emulate the remarkable human ability to learn and adapt to changes of surrounding, is now an evolving collection of methodologies including fuzzy system, neural networks and genetic algorithms, designed to exploit tolerance for imprecision, uncertain and partial truth to achieve tractability, robustness at low solution cost

    軟計算是正在發展起來的一種計算方法，它與人腦相對應，具有在不確定及不精確環境中進行推理和學習的卓越能力。軟計算有若干種計算方法構成，包括神經網路理論、模糊集合理論、近似推理及一些優化方法。
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