neural logic system 中文意思是什麼
neural logic system
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。 -
Site experiment were carried out on the testing vehicle for ahs and the magnetic markers road in national intelligent transport system center. also, study on multi - sensor information fusion and control model by using neural net system, fuzzy logic and genetic algorithm were carried out. the work completed are as follows mainly : ( 1 ) hardware system for lane keeping system including magnetic marker, magnetic sensor, control system and executor machine were designed
本文以國家智能運輸系統研究中心的自動公路系統試驗車和專用的磁軌釘道路為工作平臺，在大量的現場實驗基礎上，針對基於磁軌釘導航的車輛車道保持技術中的若干問題展開研究，運用神經網路、模糊邏輯、遺傳演算法等方法在多傳感器信息融合、控制模型等方面進行了系統的研究，主要完成了以下幾方面的工作： （ 1 ）對車道保持系統硬體平臺進行了設計，論述了導航設施? ?磁軌釘的設計過程和車載工控機、步進電機等的選擇。 -
There are many methods to gas load forecasting, including : regression analytical method, time serial method, elasticity coefficient forecasting, index analytical method, grey method, fuzzy logic forecasting, artificial neural network forecasting model, experts system forecasting model, optimizing combination forecasting model, etc.
用於燃氣負荷預測的方法很多，包括:回歸分析法、時間序列法、彈性系數預測法、指針分析法、灰色預測法、模糊邏輯預測法、人工神經網路預測法、專家系統預測法、優化組合預測法等。 -
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。 -
Professor austrom points out that fuzzy logic control, neural networks and specialist system are three typical intelligent control methods
控制學術權威austrom指出：模糊邏輯控制、神經網路和專家系統是三種典型的智能控制方法。 -
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 -
Recently, neuro - fuzzy control base on the neural network theory and fuzzy logic system was used widely and successfully
近年來，基於神經網路和模糊邏輯的神經模糊控制得到了廣泛的應用。 -
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。 -
Fuzzy neural network ( fnn ) is an active branch in the intelligent control. it is composed of the neural network and fuzzy logic system organically. and it is good at self - learning and self - tuning
模糊神經網路是將人工神經網路與模糊邏輯系統相結合的一種能處理抽象信息的網路，具有強大的自學習和自整定功能，是智能控制理論研究領域中一個十分活躍的分支，因此模糊神經網路控制的研究具有重要的意義。
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