inference network 中文意思是什麼
inference network
解釋
推斷網路-
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。 -
Evaluation of fabric wrinkle grade based on subtractive clustering adaptive network fuzzy inference systems
基於減法聚類的自適應模糊神經網路評定織物起皺等級 -
It is hard to get the important parameters such as link delay and loss rate directly, because the internet has becomes massive, distributed and heterogeneous. network tomography is now a hotspot for inference the internal link delay and loss rate with the end - to - end measurement data. we call current network tomography as unconstraint network tomography for its not adding any constraint condition and all of them nearly are based on some likelihood algorithm
由於網路日益向著大型化、異構化、分佈化發展，通過直接進行網路測量的方法，來獲得網路內部鏈路的時延和丟包率參數就變得越來越困難，網路層析成像方法作為一種通過端到端的測量數據來推斷網路鏈路性能參數的技術正成為研究的熱點之一。 -
Compared with the regular rule - based expert system, the bayesian network based es can reason on the incomplete input information using the prior probability distribution ; the topological structure of the network being used to express the qualitative knowledge and the probability distributions of the nodes in the network being used to express the uncertainty of the knowledge, which made the knowledge representation more intuitively and more clearly ; applying the principle of the bayesian chaining rule, bidirectional inference which allow infer from the cause to the effect and from the effect to the cause can be achieved
與一般基於規則的專家系統相比，貝葉斯網專家系統利用先驗概率分佈，可以使推理在輸入數據不完備的基礎上進行；以網路的拓撲結構表達定性知識，以網路節點的概率分佈表達知識的不確定性，從而使不確定性知識的表達直觀、明確；利用貝葉斯法則的基本原理，可以實現由因到果及由果到因的雙向推理。 -
The algorithm can not only eliminate the influence of the cumulative errors of the photoelectric code recorder, but also it can satisfy the requirement of the real - time control. a direct inverse model controller of fuzzy neural network with changeable structure based on takagi - sugeno inference is presented and it is used to the motion control of mobile robot. in order to avoid the obstacles successfully, detection results from ccd and ultrasonic sensors are fused by a fuzzy neural network, which acts as an avoidance controller
包括移動機器人的融合自定位問題：移動機器人利用光電編碼器進行自定位，同時用擴展卡爾曼濾波器融合多個超聲波傳感器的測量值，採用回朔演算法將融合值用於復位光電編碼器，消除了光電編碼器累積誤差的影響，並能滿足實時控制的要求：並提出一種基於takagi - sugeno模型的變結構模糊神經網路直接逆模型控制器，並應用於移動機器人的運動控制；利用模糊神經網路避障控制器融合ccd攝象機與超聲波傳感器探測到的環境信息，以實現機器人的安全避障。 -
The content of this paper is arranged as foll owing : chapter 1 introduces the concept of credit, credit risk and credit assessment, as well as the history and development of credit assessment ; chapter 2 introduces the history of ai technology, and the background of expert system and neural network. characters and disadvantages of expert system and neural network are presented respectively and the necessity of combining expert system and neural network is lightened ; chapter 3 shows the process of dealing with sample data, including the treatment of exceptional data and factor analysis, and puts forward the concrete framework of the mixed - expert credit assessment system ; chapter 4 introduces concept of object - oriented technology, and constructs object model and functional model after analyzing the whole system. it also illustrates the implementation of concrete classes by an example of rule class and the inference algorithm in the form of pseudocode ; chapter 5 introduces the structure of the whole system, the major functional models and their interfaces, and the characteristic of the system is also generalized ; chapter 6 summarizes the whole work, and points out the remaining deficiencies as well as the prospective of this method
本文具體內容安排如下：第一章介紹了信用、信用風險、信用評價的概念，回顧了信用評價的歷史、發展和現狀，並綜合各種信用評價模型，指出這些模型各自的優缺點：第二章簡單描述了人工智慧技術，著重介紹有關專家系統與神經網路的基礎知識，通過總結它們的優缺點，指出結合專家系統與神經網路構造混合型專家系統的必要性；本章還介紹了神經網路子模塊的概念，提出了混合型專家系統的一般框架與設計步驟：第三章對樣本數據進行處理，包括異常數據的剔除、因子分析等，提出了信用評價混合型專家系統的具體框架結構，介紹了系統知識庫的主要部分、基於優先級的正向推理機制的流程、以及基於事實的自動解釋機制的具體實現方法；第四章介紹了面向對象技術，進而採用面向對象對信用評價系統進行分析，建立了對象模型和功能模型，並在此基礎上，採用c + +語言以規則類為例說明系統中具體類的實現，用偽代碼的形式描述了推理的演算法；第五章描述了整個系統的結構，對系統主要功能模塊和界面進行了介紹，並總結系統的特點；第六章總結了全文，指出本文所構造系統存在的不足以及對將來的展望。 -
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。 -
Network database is adopted to store knowledge base of es and can be maintained on network conveniently. with com techniques, knowledge inference is realized in web server, and can support several users to diagnose fault at the same time
該es採用網路數據庫存儲知識，在網路環境下可以方便地實現知識庫的維護，將知識推理過程採用組件技術集成到web服務器上，可以支持多個用戶同時進行故障診斷活動。 -
On the actual ward spot, because with the variety of the season and the day and night, the environment factors is variational and with the difference of the ward spot, the environment factors is also different, based on the frame of decision level fusion this paper apply neural network and fuzzy inference technology to achieving multi - sensors fire detection system, which can endue different sensors with different weight for adapting the variation of environment according to the actual things. we test this method applied to the multi - sensors fire detection system by simulating and attain the anticipative result
針對實際監護現場，環境因素會隨著季節以及晝夜變化而變化，而且在不同的監控現場，環境因素也不相同的問題本文在決策層融合的框架下，利用神經網路和模糊推理技術相結合來實現多傳感器火災探測，根據實際情況，賦予不同的傳感器不同的權重系數以適應環境變化，通過模擬驗證了此種方法應用於多傳感器火災探測系統可達到預期效果。 -
A high - rised structural intelligent form optimization method and support system based on fuzzy inference network
基於模糊推理網的高層結構智能型式優化方法與系統 -
What flow is that, we use model simulation to analyze the em algorithm contraction ratio. through network simulating, we analyze the factors which can influence loss inference algorithm accuracy like measurement strategy or routing algorithm. we analyze the accuracy and contraction characteristic of multicast - based direct algorithm and em algorithm, and compare the error factor between them
實驗中通過網路模擬模型，確定了em演算法的收斂速率;研究了不同測量策略和路由器擁塞避免演算法對丟包率推理演算法準確率的影響;分析了單點多播的de和em演算法準確性、收斂性等特徵，通過比較兩種演算法的統計誤差，得出em演算法略優于de演算法的結論。 -
The two - stage modeling method takes into account the characteristics of software project risk management and software metrics data, integrates qualitative knowledge and quantitative data. to study the software project iterative process risk ’ s bayesian network model, the definition of cyclic bayesian network is presented, probability convergence property of directed cycle in cyclic bayesian network is proved and probability inference method is put forward
論文在軟體項目迭代過程風險的貝葉斯網路模型研究中，定義了有環貝葉斯網路，證明了有環貝葉斯網路中有向環的概率收斂性質，給出了有環貝葉斯網路的概率推理方法。 -
In order to find out a novel fuzzy inference algorithm being superior to cr1 algorithm and a novel fuzzy neural network, the author deduces nine kind of triple i algorithms by nine fuzzy operators. further more, the author compares these algorithms with the ordinary intuitional rules respectively and gives a conclusion that rl - type triple i algorithm is rather more closely to the intuitional rules. because fuzzy neural networks require the conditions of continuous and differential on membership functions of fuzzy sets and fuzzy operators of fuzzy inference, by means of comparison study, the author obtains a conclusion that the fuzzy neural networks with production operator and cr1 inference algorithm are very fit to study the problem of control
為了找出優于cri演算法的模糊推理方法和新型模糊神經網路，本文首先對常用九種模糊運算元給出了具體三i演算法，並從模糊推理的另一個方面，考察了各種演算法對日常直觀模糊推理規則的貼近程度，得出「 r _ l型三i演算法貼近日常直觀推理規則」這一結論；同時，考慮到模糊神經網路要求「網路輸出保持對模糊運算元和隸屬函數連續性、可微性」這一特性，通過比較研究，得出利用乘積運算元和cri推理的模糊神經網路最適合控制問題。 -
Cyclic bayesian network provides modeling method and inference algorithms for the management of software project iterative process risk
有環貝葉斯網路的研究，為管理軟體項目迭代過程風險提供了建模方法和模型求解演算法。 -
Temporal bayesian network and scheduling bayesian network provide modeling method and inference algorithms for the management of software project iterative process risk
時間貝葉斯網路和進度貝葉斯網路的研究，為管理軟體項目時間相關風險提供了建模方法和模型求解演算法。 -
As these methods exist shortages, advanced diagnosis strategy is presented, which combines the fuzzy neural network instead of fuzzy inference to rules inference. the problem of accuracy ratio decline because of roughness of fuzzy synthesizing algorithm has been solved. an example of car diagnosis is given and validity of this method has been proved
因此本章提出了以模糊神經網路代替模糊推理並與規則推理相結合的先進診斷策略，解決了因模糊合成演算法的粗糙性使診斷成功率下降或診斷錯誤的問題，並給出了一個車輛故障診斷實例，驗證了上述方法的正確性和有效性。 -
The congestion probability of switcher can be gotten by inference of belief network model with the statistical data of simulation
通過對交換機模擬統計阻塞參數，並使用信度網模型預測交換結點的阻塞概率。 -
Bayesian inference network
貝葉斯推理網路 -
A new fuzzy identification approach for complex systems based on neural - fuzzy inference network
一種新的基於神經模糊推理網路的復雜系統模糊辨識方法 -
It improves traditional positive inference. based on topology structure of power network in power system database, a inference network graph is established with the method form top to bottom. a positive inference is used in inferring and the positive inference algorithms is proposed
對傳統的正向推理演算法進行了改進，以網路數據庫中電網拓撲結構作為前提，採用自下而上的方法建立推理網路圖，採用正向推理機制進行推理，並給出了正向推理演算法。
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