neural system of logic 中文意思是什麼
neural system of logic
解釋
神經邏輯系統-
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。 -
The evaluation of contactor performances according as dynamic characteristic curves is put forward the first time. fuzzy logic and neural network are introduced to establish a model for the contactor performances intelligent evaluation system. the model mentioned above can give a performance evaluation result in the meanwhile of the contractor dynamic process testing
首次提出以動態特性曲線參數作為接觸器性能評判的依據，並構造了基於模糊聚類分析和神經網路演算法的接觸器動態特性性能評判模型，在實現對接觸器動態過程測試的同時，給出接觸器動態特性性能評判結果。 -
The artificial neural network provides convenient and fast tools to simulate rice growth and gets ride of the limitation of traditional models. 4. fuzzy discrimination system of photothermal traits was developed with fuzzy logic theory and matlab 5. 1
4 、在水稻高產栽培專家系統的基礎上，利用模糊邏輯的理論和方法，以matlab5 . 3為編程工具，研製了水稻光溫生態特性的模糊鑒別系統，試圖提高專家系統的功能。 -
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。 -
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。 -
Reviews and analyses have been done aiming at the three main branches of intelligent control of fuzzy logic control, neural neuwork control and expert control system
對智能控制的3大主要分支模糊邏輯控制、神經網路控制及專家控制系統在污水生物處理中應用的最新動態進行了評論和分析。 -
Specialist system faces many problems and difficulties, such as knowledge acquirement depends on manual transplantation which leads to high cost and low efficiency ; applying general clarified set brings forward with feeble reasoning ability, matching collision and combination explosion. nowadays modern intelligent control focuses on fuzzy logic and neural networks or the combination of the two
由於專家系統在實際應用中有較多的問題和困難（如：知識的獲取主要靠人工移植，因此成本高、效率低；採用常規的分明集，致使它的推理能力弱，容易產生匹配沖突、組合爆炸等問題） ，現在智能控制的重點則集中在模糊邏輯、神經網路以及二者的結合應用上。 -
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。 -
In the constructing of the diagnosis module using the technology of the combination of the fuzzy logic and neural network, which based on the fuzzy adaptive learning control network, a simple kind of capable method for consummate the structure and performance of network is introduced, which includes the rules extraction based on the maximum weights matrix and the parameters amendment based on genetic algorithm by floating - point coding. during the monitoring of the parts condition, the output of the condition monitoring system shows the good working condition of the executing agency by fuzzily deducing from the control instruction send by the auv ' s controller and motion status, and so offers the proof to complete mission and return safely
在珍斷模塊建模中採用模糊邏輯與神經網路結合的技術，以模糊自適應學習控制網路為核心，提出了一種簡單可行的基於最大權值矩陣的規則提取及基於浮點數編碼的遺傳演算法的參數調整的，完善網路結構與性能的方法，並在狀態監測過程中，通過對由控制器輸入的水下機器人運動控制量以及運行狀態的模糊推理，得到執行部件（推進器或舵）的工作狀態優劣程度，為保證水下機器人完成任務，安全返回提供控制依據。 -
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。 -
So the paper combined the fuzzy logic control and recurrent neural network, and the recurrent fuzzy neural network ( rfnn ) controller is introduced into the speedsensorless vector control system. moreover, an online parameter training methodology, which is derived from the lyapunov stability theorem and gradient descent method is proposed to increase the learning capability of the rfnn. the rfnn controller has a better performance than the pi controller system ; the effectiveness of the proposed control scheme is verified by simulation results
因此論文將模糊控制和具有優越動態性能的遞歸神經網路結合起來，取長補短，提出了一種遞歸模糊神經網路控制方法，利用神經網路來實現模糊推理，可動態的調整隸屬函數的形狀、位置以及神經網路遞歸權值，並對其與pi控制器的交流調速控制系統進行了模擬比較，模擬結果表明與普通的pi控制器相比較，遞歸模糊神經網路控制器有較好的動態性能，控制器的收斂速度快、靜差小，系統在遇到參數發生變化和外部不確定性問題時魯棒性、抗擾動性有明顯的提高。 -
It adopted a bp neural network with a lag factor to identify the counter static model of process and decided parameters of feed - forward control through a model image, adopted a feedback controller that can adjust fuzzy logic according to the changes of object ' s parameters to improve dynamic control effect and adopted a control strategy simulating human intelligence to harmony works of system by switching among each control combination
它採用加滯后因子的bp神經網路辨識對象的靜態逆模型，並通過模型映射直接決定前饋控制的參數；用可隨對象參數變化調整模糊邏輯的閉環控制器配合前饋控制器以改善動態控制效果；用仿人智能控制策略協調系統的操作，在各種組合控制方式之間進行切換。 -
Fault diagnosis and alarm system of industrial process based on neural network and fuzzy logic
基於神經網路和模糊邏輯的工業過程故障診斷與報警系統 -
The three main methods ( neural network, fuzzy logic system and ga ) of intelligent control are studied in the paper, and they are proved to be reasonable and practical
本文對智能控制中的三個主要方法神經網路、模糊邏輯和遺傳演算法在船舶動力定位系統中的應用進行了全面的分析和研究，並通過模擬實驗驗證了所研究技術的合理性和實用性。 -
Then employing neural networks learning techniques, fuzzy logic rules, input - output fuzzy membership functions and weights in networks can be easily tuned. so rule matching is reduced, inference process is accelerated, adaptability of the system is greatly improved
再利用神經網路學習能力便很容易修改規則庫中的模糊規則以及隸屬函數和網路權值等參數，這樣大大減少了規則匹配過程，加快了推理速度，從而極大程度地提高了系統的自適應能力。 -
Then, the cc - pwm linear current control strategy is also studied in detail in this paper, and two improved self - adaptive pi controllers are brought forward on the basis of fuzzy logic control theory and fuzzy logic neural network control theory which sufficiently takes advantage of self - learning capability of neural network. they can greatly improve the dynamic performance and cc - pwm system can achieve fast system dynamic response
論文深入研究了cc - pwm逆變器的線性電流控制策略，並提出了模糊自整定pi控制和基於神經網路的模糊推理自整定pi控制兩種改進型智能pi控制演算法，其中的模糊神經網路pi控制演算法充分利用了神經網路具有很強的自學習能力的特點。 -
This part contained three subjects : designing and optimizing fuzzy logic controllers ( flc ) and artificial neural networks ( ann ), fuzzy neural network model identification of complex system
主要包括模糊控制器與人工神經網路的優化設計，以及具有不確定性的復雜系統的模糊神經網路模型辨識三個方面。 -
It can complete the logic deduction procession using the theory of neural computing. last, the different functional parts of the diagnosis system are discussed
最後，本文分別介紹了該故障診斷系統的各功能模塊，並完成了診斷系統的合成。 -
The simulation results show that, the evolution architectures model win the advantage of integrating the research production such as natural language proc essing, fuzzy logic, neural network techniques, artificial intelligent and intelligent deciding methods easily. in other words, it will take full advantage of the operators " subjective value, provide an intelligent assistant deciding environment to all levels managers, and boost the information processing ability and command & deciding levels. those advantages are attributable to that the evolution data fusion architectures are founded on the physical base of anthropic thinking and deciding, i. e., the evolution theory of nervous system
研究表明，由於直接以人類思維與決策的物理基礎，即神經網路進化的理論為基礎建立數據融合體系結構模型，數據融合系統的進化體系結構更有利於集成諸如自然語言處理、模糊邏輯、神經網路技術、人工智慧和智能決策等方面的研究成果，它可以充分發揮指揮和操作人員的主觀能動性，為各級管理人員提供一個智能化輔佐決策環境，提高復雜網路系統的信息處理能力和指揮決策水平。 -
In the neural networks control, the structure and the working principle of the cerebella model articulation controller ( cmac ) are discussed firstly, and then based on the mutual supplements and the similarities between fcmac and fuzzy logic, fuzzified cerebella model articulation controller ( fcmac ) is proposed. the learning control system based fcmac are introduced in detail. through the example of fcmac used in the swinging up a pendulum control, the excellent control effects are demonstrated
在神經網路控制方面，本文主要研究了小腦模型關節控制器（ cmac ） ，並進而根據cmac與模糊邏輯的互補性與相似性，提出了模糊小腦神經網路控制器（ fcamc ） ，詳細討論了fcmac的學習控制系統與fcmac的自學習機理，通過fcamc對倒單擺控制的具體例子表明， fcmac控制具有優良的控制效果和強的魯棒性。
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