knowledge and neural network 中文意思是什麼
knowledge and neural network
解釋
知識和神經網路-
Expert system has many merits. it has the ability of heuristic illation, and can explain for illation and append new knowledge in the knowledge database. but it also has obvious shortcomings, such as, poor ablitity in ka ( knowledge achieve ), inefficient and incomprehensive. the artificial neural network has the ablitity of parallel processing, associative memory, distributed storage of knowledge and high robust etc. it also has perfect characteristics of self - organizing, self - adaptive, self - learning. it specializes in visualize ideation but is short of logic ideation
專家系統在故障診斷領域得到廣泛的應用，專家系統具有許多優點，能利用專家的知識進行啟發式推理，能夠解釋其推理過程，並能夠不斷地、靈活地增加新的知識。但專家系統也存在明顯的缺陷：獲取知識能力差、效率低、范圍窄。可以說專家系統長于邏輯思維缺乏形象思維。 -
Since human ' s knowledge of real neural system is very limited, the improvement and development of artificial neural network need more detail information from neurophysiology and neuroanatomy
由於人類對真實神經系統只了解非常有限一部分，人工神經網路的完善與發展有待于神經生理學、神經解剖學的研究給出更加詳細的信息和證據。 -
Procreant knowledge expression and forward inference engine are adopted in the method of fault diagnosis based on expert system theory. in the fault diagnosis applying neural network theory, six kinds of improved arithmetic of back - propagation arithmetic, including gradient descent with momentum, variable learning rate back - propagation, resilient back - propagation, quasi - newton, levenberg - marquardt and conjugate gradient, are applied to diagnose the faults of electric load manage center and solid state power controller. different diagnostic results gotten by simulation are compared at last
在基於專家系統的故障診斷方法中，採用了產生式知識表達和正向推理機制；在基於神經網路的故障診斷方法中，則分別採用了bp神經網路的附加動量法、自適應學習速率、彈性bp演算法、擬牛頓法、共軛梯度法和levenberg - marquardt法對電氣負載管理中心和固態功率控制器的故障進行診斷，並對由模擬得到的不同診斷結果進行比較。 -
Wavelet analysis and neural network have been researched. based on bp neural network, analysing the features of the bp neural network ' s activation function and the structure of the bp neural network, wavelets neural network is constructed with wavelet function. fourier transform has a important role on signal processing, so the fourier transform is introduced. a function ' fourier transform is analysed. after introducing the concept of the wavelet analysis, a serval wavelet functions is given out, so the knowledge of wavelet analysis is better understood. the multiresolution analysis has a important role on constructing wavelet function and understanding the wavelet transform
小波分析和神經網路得到了廣泛的研究，小波神經網路是在bp神經網路的基礎上，考慮和分析了bp神經網路的激勵函數的特點，以及bp神經網路的結構，結合了小波分析的知識而構造的。傅里葉變換在信號的處理起重要的作用，所以介紹了傅里葉變換、離散傅里葉變換和加窗傅里葉變換，並對一函數作離散傅里葉變換分析。 -
This thesis introduces the working principle, craftwork requirement, modeling process, control strategies and the realization of lf refining furnance bottom blowing argon control system. through the study and analysis of bottom blowing argon process control system, the thesis discusses the mean neural network model of controlled object and the mathematical models of the exectors, pwm adjustable pressure controller and pcm adjustable flux controller according to the relevant liquid knowledge and relevant data, including design data, test data and running data. to begin with the craftwork reguirement of bottom blowing argon and the actual instance of the control system, it presents the strategies of fuzzy parameters self - adaptive pid control used in pressure difference inner loop and fuzzy plus pi compound control used in flux outer loop which are based on the above modeling in order to carry out the accurate control of argon flux
本文介紹了lf精煉爐底吹氬過程式控制制系統的工作原理、工藝要求、建模過程、控制策略以及控制系統的實現。通過對精煉爐底吹氬過程式控制制系統進行研究與分析，並根據流體力學的有關知識以及有關數據（其中包括設計數據、試驗數據和運行數據） ，建立起了被控對象的平均神經網路模型和執行機構（即pwm調壓器和pcm調流器）的數學模型。在此模型的基礎上，從底吹氬工藝要求和控制系統的實際情況出發，提出了壓差內環模糊參數自適應pid控制策略和流量外環模糊pi復合控制策略，以實現氬氣流量的精確控制。 -
Visual rice growth models ( vrgm ) and rice expert system of cultivation management for high yield were established by synthesizing the results of " national rice project " and combining the cultivation knowledge, experience of experts, while the techniques of artificial neural network and fuzzy logic were employed to improve the rice growth models and the expert system. the main results are as follows
本研究系國家「九五」攻關項目「水稻大面積高產綜合配套技術研究與示範」課題的子專題，結合水稻高產栽培技術資料和水稻專家的知識、經驗以及科研成果，研製成了可視水稻生長模型（ visualricegrowthmodels ， vrgm ）及水稻高產栽培專家系統，並在此基礎上進一步利用人工神經網路模型、模糊邏輯技術和田間栽培試驗，對生長模型和專家系統進行了改進。 -
Finally the control result is improved by the output of fnnc. another neural network called pnn is introduced to finish constructing and renovating the knowledge database
本文主要對模糊神經網路自組織控制器在自動舵中的應用進行了研究，綜合了模糊控制和神經網路的應用。 -
One is field fault diagnosis system, whose core arithmetic is back propagation neural network ; the other is remote fault diagnosis system, whose core arithmetic is fault tree. in this system, the database was used to save the fault knowledge and related information
現場診斷的核心是神經網路技術，通過對bp神經網路的分析，初步建立了檢測線的神經網路診斷系統，並以制動臺的故障監測與診斷為例，重點介紹了建立過程及診斷效果。 -
In the paper, the following main factors are studied, such as developing the expert knowledge - base based on the special knowledge of the explosive demolition of frame building, designing the object - oriented expert system of the explosive demolition of frame building, developing the neural network training example base based on projects, developing the forecasting mode of blast effects with matlab 6. 1, developing the expert system of explosive demolition of frame building with visual b 6. 0, carrying out the connection of the expert system and forecast mode. the system consisted of eleven functional modules, such as the input of initial parameters module, the choice of the blasting method module, the choice of blast mode module, the design of blasting parameters module, the design of charge module, the verifying blasting safety module, the calculating safety of tumble module, the design of detonating net module, the blast effects forecasting module and the calculating volume module
本文的研究內容有：以框架結構樓房拆除爆破領域的專業知識為基礎製作專家系統知識庫；設計一般面向對象的框架結構樓房爆破拆除設計的專家系統；搜集相關爆破工程實例製作用於爆堆效果預測神經網路訓練的樣本數據庫；選取適當的輸入輸出因素，用matlav6 . 1構建爆破效果預測神經網路模型；用vb6 . 0編程開發出框架結構樓房拆除爆破專家系統，並實現爆破效果預測神經網路模型和專家系統的鏈接。該系統由初始參數輸入、倒塌方法選取、倒塌方案確定、孔網參數設計、缺口形狀及參數、爆破安全校核、傾倒安全校核、爆破網路、爆破效果預測、工程量計算、計算設計說明書等十一大功能模塊組成。 -
This article introduces the developing history and the current situation of the automatic goal discern, and on the basis of structure of the parallel computer and neural network knowledge, it analyses the hardware and software engineering foundation that realized the real - time goal recognition system
介紹了自動目標識別的發展歷史和現狀，在并行計算機結構和神經網路知識的基礎上，分析了實現實時目標識別系統的硬體和軟體技術基礎。 -
Fourth, after the characters of neural network, fuzzy technology and expert system were analyzed three models about combining expert system and neural network and their respective applied condition have been proposed. the methods of using fuzzy knowledge in expert system and combining neural network and fuzzy logic have also been discussed
第四，在對專家系統、神經網路和模糊技術各自的特點進行深入地分析之後，本論文提出了將專家系統和神經網路相結合的三種模型，分析了各模型所適用的環境，並討論了對符號專家系統進行模糊化改造以及模糊邏輯同神經網路相結合的方法。 -
To be concrete, the principle of the system is just like this. whether breakout occurs or not is judged by expert system using two kinds of knowledge : neural network and knowledge base
具體來說，本系統的原理就是將神經元網路的輸出和知識庫的知識輸入到專家系統中來，由專家系統來進行綜合評判，判斷是否會發生漏鋼事故。 -
Neural network is applied in design of blast parameter, which is not needed the trim and sum up of engineer and knowledge of expertise. what are needed is some succeed examples and stylebooks to train the system. to some knowledge, which is expressed by implication, at the same time to acquire knowledge, much knowledge in the same question were showed in the same network
採用神經網路進行爆破參數設計不需要知識工程師進行整理、總結以及消化領域專家的知識，只需要用領域專家解決問題的實例或範例來訓練網路；在知識表示方面，採取隱式表示；在知識獲取的同時，自動產生的知識由網路的結構和權值表示，通用性強，便於實現知識的自動獲取和并行聯想推理。 -
The combination of fuzzy theory and neural network theory can improve the intelligence level of strategic manangement fifth, the process of strategic manangenietn is the process of knowledge creation and knowledge application, the ultimate objective of the system is to nurture knowledge advantage
論文通過模糊理淪和神經網路的結合，構造戰略制定模型，以提高錢略管理系統的智能水平。 （ 5 ）戰略管理過程就是企業確立知識優勢力的過程。其系統運行的目標就是培育知識優勢力。 -
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。 -
Based on the neural network structure in the paper, the object - oriented knowledge representation thought about neural network is deeply discussed and this paper trys to realize it with the neural network structure. to some extent, it is realized, but not mature, this paper just puts forward an idea, and gives some sugestions. at last, the paper prospects the coming researching work
目前來看，以文中的網路結構，只能一定程度的實現這一思想，因此，在展望中希望能夠進一步完善這種組建神經網路的思路，比如，可以採用結合異聯想神經網路（ bam ）來實現對象屬性空間的轉移，從而建立對象屬性之間的推理機制。 -
With the help of dynamic qualitative information of working marine diesel power equipment in this field and expertise, a new long - distance oil monitoring expert system of marine diesel power equipment has been proposed and developed with the characteristic of expounding the dynamic features of marine diesel power equipment from the perspective of chaos knowledge, possessing intellectualized auxiliary decision - making mechanism based on fuzzy reasoning and neural network reasoning, utilizing mathematic analysis model established by means of track facility states of chaos vector and capable of evaluating the analysis results of oil monitoring facil ity ' s development of engine power and its working conditions accurately
然後，結合廣泛搜集的本研究領域內船舶柴油機動力裝置在運行中的動態定性信息與專家經驗，研製開發了運用混沌學的觀點闡釋船舶動力裝置的動力特性，並擁有基於模糊推理與神經網路協作推理的智能化輔助決策機制，採取通過求取設備狀態混沌向量等方法建立的數學分析模型進行數據分析，能準確地評價船舶柴油機動力裝置油液監控設備狀態變化趨勢及其運轉狀況的遠程輪機油液監控診斷專家系統。本文研製開發的遠程輪機油液監控診斷專家系統在internet intrabet網路環境下，具有遠程智能專家診斷的特點。 -
Data mining ( dm ) aims at drawing implied and useful information / knowledge from massive incomplete, noisy, blurry, and stochastic real data ; while neural network is a frequently used tool for dm
數據挖掘就是從大量不完全的、有噪聲的、模糊的、隨機的實際數據中發現隱含的、事先未知的潛在有用的並且最終可理解的信息和知識的過程。 -
It gives many important helps to enhance the security of the control system. the first chapter of this paper gives a brief introduction to the development of fault diagnosis and the basic knowledge of it. the second chapter dicusses the fault diagnosis based on the expert system. the third chapter introduces the fault diagnosis based on the fault tree analysis. the forth chapter gives the fault diagnosis based on the fuzzy system. the fifth chapter analysis the fault diagnosis based on the artificial neural network in detail. the last chapter is the most important part of the paper, in this chapter i give a new fault diagnosis based on the fuzzy neural network, and applicated it in the kj15a control system, obtain the good result
本文的第一章介紹了故障診斷的發展概況與一些故障診斷的基本知識；第二章討論了基於專家系統的故障診斷；第三章論述了基於故樟樹分析法的故障診斷；第四章給出了基於模糊系統的故障診斷；第五章詳細分析了基於人工神經網路的故障診斷；第六章是本文的核心部分，它在綜合了前面的模糊系統和神經網路故障診斷的基礎上，提出了一種基於神經模糊網路故障診斷，並將該技術應用到「 kj15a礦井機車運輸監控系統」故障檢測上，取得了良好的效果。 -
Analyses the incompleteness of medical diagnosis experts knowledge and discusses the method of integrating expert system with neural network for the representation and acquisition of expert knowledge, and the single parameter dynamic searching algorithm which acts as the studying algorithm of neural network and works better than bp algorithm, and then presents an intelligent medical diagnostic system designed by integration of expert system and neural network for clinical diagnostic purpose and concludes from test the results that the method of integrating expert system with neural network is effective for representation and acquisition of expert knowledge for medical diagnosis system
討論了神經網路理論在智能醫療診斷系統方面的應用，在分析醫療診斷專家知識不完備性的基礎上，研究了適應醫療診斷系統專家知識表達與獲取的專家系統與神經網路集成方法.提出了採用單參數動態搜索演算法訓練神經網路，其效果明顯優于傳統的bp演算法.設計了專家系統與神經網路集成的心血管疾病智能醫療診斷系統，在臨床實踐中取得了較好的效果，證明專家系統與神經網路的集成是醫療診斷系統專家知識表達與獲取的有效方法
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