fuzzy expert network 中文意思是什麼
fuzzy expert network
解釋
模糊專家網路-
The thesis presents a expert system for identifies power quality disturbance signal, after compare the artificial neural network, nearest neighbors, fuzzy decision, and expert system. we bring forward the project flexible rule - based expert system, according to the characteristic inspection and measure system, and has a deep research on the problem of this system. this project for disturbance classifies has lower mistake ratio and facility maintenance
採用專家系統的方法進行模式識別，在對神經網路、最近鄰法、模糊邏輯和專家系統及一些交叉方法等模式識別方法進行比較分析的基礎上，根據電能質量信號故障分析的特點，提出了採用規則基專家系統的方法，該模式識別方法具有便於擴展、修改和識別率高等特點。 -
Expert system based on fuzzy neural network for the optimal control of blank holder force
神經網路簡化模型設計多變量自適應模糊控制器 -
Network forensics is an important extension to present security infrastructure, and is becoming the research focus of forensic investigators and network security researchers. however many challenges still exist in conducting network forensics : the sheer amount of data generated by the network ; the comprehensibility of evidences extracted from collected data ; the efficiency of evidence analysis methods, etc. against above challenges, by taking the advantage of both the great learning capability and the comprehensibility of the analyzed results of decision tree technology and fuzzy logic, the researcher develops a fuzzy decision tree based network forensics system to aid an investigator in analyzing computer crime in network environments and automatically extract digital evidence. at the end of the paper, the experimental comparison results between our proposed method and other popular methods are presented. experimental results show that the system can classify most kinds of events ( 91. 16 ? correct classification rate on average ), provide analyzed and comprehensible information for a forensic expert and automate or semi - automate the process of forensic analysis
網路取證是對現有網路安全體系的必要擴展，已日益成為研究的重點.但目前在進行網路取證時仍存在很多挑戰:如網路產生的海量數據;從已收集數據中提取的證據的可理解性;證據分析方法的有效性等.針對上述問題，利用模糊決策樹技術強大的學習能力及其分析結果的易理解性，開發了一種基於模糊決策樹的網路取證分析系統，以協助網路取證人員在網路環境下對計算機犯罪事件進行取證分析.給出了該方法的實驗結果以及與現有方法的對照分析結果.實驗結果表明，該系統可以對大多數網路事件進行識別（平均正確分類率為91 . 16 ? ） ，能為網路取證人員提供可理解的信息，協助取證人員進行快速高效的證據分析 -
By the browser / web server / database structure and the technology of asp. net and xml, we achieve the expert system running on the network, extend the application and ensure its backward compatibility ; we have the deep research to the representation of knowledge and apply it to the system, extend the traditional method of rule based knowledge representation ; introduce the fuzzy sets, analyze the generalized possibility interval sets, and combine the linguistic variables and fuzzy sets ; the system adopts the forward and backward chaining, researches the reasoning under uncertainty and inexact reasoning ; and we depart knowledge base and inference engine, make the upgrade simple and maintenance convenient. in the last, we construct the potato produce manage system according to the phases of potato ' s growth to give a detailed instruct to its produc e
Net和xml技術，實現了網路化的專家系統，同時擴大了專家系統的應用范圍，提高了系統的後向兼容性；對專家系統中的知識表示技術作了深入探討，在傳統的基於規則的知識表示方法的基礎上，提出了基於規則擴展的知識表示方法，並較好地將其應用到本系統中；引入了模糊集合，分析並推導了廣義可能區間集，將其應用於模糊知識的表示，將語言變量和模糊集合結合起來；提出對系統採用互動式知識獲取途徑、雙向推理控制策略，對不精確推理和不確定性推理的傳播演算法作了一定的研究，成功地將其應用到馬鈴薯專家系統的構建之中；採用知識庫和推理機相分離的方法，使得系統升級簡單易行。 -
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。 -
Then, a practical approach of software quality evaluation based on this model is given out which uses the network method of nerve and combines the associative memory model with the expert judge and fuzzy appraisal according to the gradient theory. and a program of this approach is compiled using c #. net
然後，根據梯度理論，應用神經網路方法將聯想記憶模型與專家評判、模糊評價相結合，給出一個基於此模型的軟體質量評價的實用方法，並用c # . net對此評價方法編程實現，最後通過實例來說明此方法。 -
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。 -
On the basis of existing research, the paper integrates fuzzy neural network technology with diagnosis expert system based on case - reasoning and rule - reasoning
本文在已有研究基礎上，將模糊神經網路技術集成到基於實例推理和規則推理的診斷專家系統中。 -
Due to the fact that the structure of internal combustion engine is complex, fault diagnosis cannot be made in a single way and human intelligence diagnosis technique making use of information interinfiltrate and neural network and fuzzy logic and expert system must be adopted in order to obtain high accuracy and real time
由於內燃機結構較為復雜，因此只用單一方法對它進行診斷是不夠的，必須藉助于信息融合、神經網路、模糊邏輯以及專家系統等人工智慧技術的計算機診斷方法，才能達到較高的準確性及實時性。 -
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。 -
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。 -
Also, the experiments show that when the hme, which is a mixture of the fuzzy network and the expert system based on knowledge, is used to diagnose the fault of the boiler, some points can be attained : both symbol reasoning and nerve network reasoning can be combined very well
同時，實驗結果還表明將模糊網路技術與基於知識的專家系統技術結合的分層混合專家網路應用於鍋爐故障診斷，能實現符號推理與神經網路推理的有機結合，層次清晰、推理效率較高。 -
( 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。 -
However, the traditional expert systems only handle the dominant and superficial knowledge, they have lots of demerit such as weak reasoning ability, poor intelligence and the difficulty in getting knowledge and so on. therefore, this paper introduces the technology of the artificial neural network ( ann ) to overcome the shortage of expert systems, and tries to solve the problem which has complicated relationship, fuzzy boundary questionably factor and expresses hard in regulation and mathematical model
但傳統專家系統只能處理顯性的表面的知識，存在推理能力弱，智能水平低，而且知識獲取難等缺點，所以本文引入了人工神經網路技術來克服傳統專家系統的不足，來試圖解決農業系統中存在的關系復雜、邊界模糊、不確定性強等難于用規則或數學模型嚴格描述的問題。 -
Secondly, the combination of fuzzy logic, neural network and expert system technology etc. has been in progress research, the structure and realization of the fuzzy expert system based on fuzzy bp neural network have been presented, carrying on the comparison and analysis with the traditional expert system
其次，對模糊邏輯、神經網路和專家系統等技術的結合進行了研究，給出基於模糊bp神經網路的模糊專家系統結構，並對其實現進行理論方面的研究，同時將它與傳統專家系統進行比較分析。 -
In this paper, after analyzing the three layer structure of data fusion system, then a kind of fire detection ' s three - layer structure based on data fusion is proposed. also according to fire ' s non - structure character, proposes to use artificial intelligence method in fire detecting three layer structure, mainly including expert system, neural network and fuzzy control technology. the aim is to design a kind of quickly, exactly and effectively fire detecting system
本文在分析了數據融合系統的三級結構及火災非結構特性的基礎上，提出了一種基於信息融合的火災探測三級結構和實現三級結構的人工智慧演算法，這些人工智慧演算法主要針對於火災的非結構特性，包括專家系統、人工神經網路、模糊控制等人工智慧技術，目的在於設計出一種快速、準確和有效的火災探測系統。 -
It explains how to building expert system with a neural network, virtual instrument and fuzzy cluster algorithm. at the last of the paper, the write shows an example of the development for such a system
對于專家知識的獲取和知識的系統應用是一種很好的嘗試，較好的解決了知識獲取的窄瓶頸問題。 -
Second, owing to the wide application of the expert system, there is also a variety of models applied for combining neural network, fuzzy technology and expert system in different fields
其次，由於專家系統的應用領域非常廣泛，所以將神經網路、模糊技術同專家系統結合起來應用於不同領域的模型也多種多樣。 -
A method to generate assembly sequences using hierarchical probabilistic fuzzy cognitive map ( hpfcm ) based on expert knowledge was developed based on the assembly information of products and a network graph extracted and drawn by a 3d software ug
摘要提出在三維軟體ug二次開發提取產品裝配信息並建立網路圖的基礎上，基於專家知識建立層次概率模糊認知圖來產生裝配序列。 -
For the extend model of cognitive map, conditional probability, theory of uncertainty and knowledge database are introduced to cognitive map, and fuzzy cognitive map ( fcm ), probabilistic fuzzy cognitive map ( pfcm ), belief knowledge database based probabilistic fuzzy cognitive map ( bkpfcm ), " extended dynamic cognitive network " are presented. therefore, those extended models can express the fuzzy and belief measure of uncertainty causal relationships and expert knowledge with uncertainty
本文把條件概率、不確定性理論及知識庫引入認知圖中，提出「概率模糊認知圖」 、 「基於信任知識庫的概率模糊認知圖」及「擴展動態認知網路」來表示事物間因果關系測度的不確定性、因果聯系的時空特性及專家對知識的不確定性，從而擴展了認知圖模擬現實世界的能力。
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