fnn 中文意思是什麼

fnn 解釋
模糊神經元網路
  1. Because aitken transform can not converge in many conditions, this paper presents an improved algorithm fnn - aitken extrapolation algorithm by analysis the reason of instability

    為了彌補該演算法的缺陷，本文在分析了該演算法不穩定性的根源后提出了改進演算法fnn - aitkenextrapolation 。
  2. Hydraulic control system of double - cylinder vessel gate is a sort of typical electrohydraulic proportional control system0 in order to study electrohydraulic flux control characteristics of this system, i have analyzed the principle of this hydraulic control system, and made its mathematics model ? in double - cylinder hydraulic system, it is necessary to process electric synchronous control in this hydraulic system, this paper also introduces a sort of fnn ameliorated from the point of view of intelligent control theory, and clarifies the principle of applying that network to achieve synchronous controlo at the same time, the means of fuzzy configuration analysis is used for network training, the comparative experiments make known that the method of applying fnn to realize synchronization control is feasible, furthermore, its effect is better than others0 this paper puts forward that a distributed control system can be used to monitor and control vessel gate within a real - time or remote distance, the basic project, structure, applications and functions of computerized scada system in hydraulic system of vessel gate is introduced ? a double layer network structure, epigynous and hypogynous machine network, is applied to this system, in accord with the application of technique such as plc, integrated software etc, this paper introduces the methods and application to achieve the computerized scada system in the task, and analyzes the characteristic of this system, in this paper, the application of configuration in monitor and control system of vessel gate is discussedo in addition, in accord with the application of technique such as visual basicb

    雙缸船閘液壓啟閉控制系統要求解決同步控制問題，文中從智能控制理論角度出發，採用了一種改進的模糊神經網路，結合模糊聚類分析方法，闡述了應用該網路實現同步控制的原理。通過對比模擬實驗表明：應用模糊補經網路實現同步控制是可行的，而且它的同步控制效果要優于傳統的設置主從令缸控制方法，具有良好的魯棒性能。另外，本文提出了建立船閘控制系統的分散式控制系統，介紹了船閘液壓控制系統的計算機監控系統（ scada ）的方案、結構、應用和主要功能，採用雙層網路化結構：上位機網路和下位機網路，並結合plc通信網路技術和組態軟體等技術構成的計算機監控系統的實現方法，實際應用，分析了這種較新的系統模式在船閘液壓控制系統的計算機監控系統的功能實現中所具有的特點。
  3. To overcome the limitations of general fnns and bp algorithm, this thesis introduced a hybrid feed - forward neural network, which is composed of a linear model and a general multi - layer fnn, and proposed a new learning algorithm for the hybrid fnn

    其次，針對bp網路存在的缺陷，結合前向神經網路和線性最小二乘法的優點，構造了一種基於混合結構的神經網路，提出了相應的非迭代的快速學習演算法。
  4. The fuzzy layer of the hybrid fnn include two kinds of neurons, one is gaussian fuzzification neuron which used to give the continuous input an fuzzy membership value, another is a presented fuzzy cluster neuron which also used to give the discrete input an fuzzy membership value

    該混合模糊神經網路的模糊化層除了具有模糊化神經元，還加入一類模糊聚類神經元。模糊聚類神經元通過預先計算的模糊聚類隸屬度矩陣來輸出對應于離散輸入的模糊化值。
  5. To verify the effectiveness of the proposed hybrid fnn, this thesis addressed the estimation problem for the frozen point of light cyclic oil in a fluidized catalytic cracking unit ( fccu ) in a refinery. based on the sample data collected from the industrial unit, we built a soft sensor model by using an above hybrid fnn

    最後，針對某煉油廠催化裂化裝置主分餾塔輕柴油凝固點的軟測量估計問題，本文基於工業現場所採集的樣本數據，建立了混合結構神經網路模型，並討論該模型的在線自學習問題，同時與多層前向bp網路、徑向基函數rbf網路模型進行了比較。
  6. Based on the disaggregate model thought, a traffic modal splitting model based on fnn is proposed, and the passenger quantity partaking proportion of urban railway transit and transferring passenger quantity proportion in hub station are fixed by fnn model

    基於非集計模型的思想，建立一種基於模糊神經網路（ fnn ）的交通方式劃分模型，並利用fnn模型對軌道交通客流分擔率和軌道交通樞紐站內與交通方式的換乘比例進行劃分。
  7. There are many types fuzzy - neural network at present. but in this paper, a new type of fnn structure is presented which is in form of series

    模糊神經網路的種類很多，本文在總結模糊神經網路的發展與分類的基礎上提出了一種新型的模糊神經網路串聯式結合方式。
  8. 4. we use the fuzzy neural networks ( fnn ) theory to solve the real time region traffic distributed control problem. at each intersection, we set an intelligent controller which dynamicly manages phase sequences, phase switch, signal cycle and split

    每個交叉口設置一個模糊控制器，該控制器根據它自己和相鄰交叉口的交通流信息對相序、相位切浙江大學博士學位論文換、信號周期和綠信比進行動態管理。
  9. The theory of fuzzy neural network ( fnn ) modeling for nonlinear systems is presented

    摘要論述了模糊系統和神經網路相結合的非線性系統辨識理論。
  10. The new fnn controller not only has the fuzzy controller ' s characters of simple structure and easily - used, but also has the self - study ability of the elman network. thus it is valuable for research for non - linear system. in this paper, it summarizes the development of dc - dc converter firstly, and presents a new idea which is using fuzzy - neural network in dc - dc converter

    這種串聯型模糊神經網路具有模糊控制的結構簡單、設計簡便及使用方便的特點，同時又利用了人工神經網路的聚類功能，使整個控制器又具備人工神經網路的自學習能力，因此這種串聯型模糊神經網路具有了良好的智能控制功能，特別適合於在非線性系統中的應用。
  11. Then an impedance control strategy with robust performance is presented aiming at uncertainties of robot, fnn is used to learning the uncertainties in order to eliminate disturbance, which have good robust and high value in practice. finally, an adaptive method is presented

    為此，本文又在機器人阻抗控制的基礎上，針對機器人和環境的不確定性，提出一種具有魯棒性的阻抗控制結構，使用模糊神經網路作為補償控制器消除力控制中的所有不確定性，具有較強的魯棒性和較好的實用價值。
  12. 4. it is used fuzzy neural networks ( fnn ) of the intelligent theory to control the formation process. in order to realize the real - time control, we use the compensatory learning algorithm

    第四，將智能控制理論中的模糊神經網路控制方法引入發酵過程式控制制，為了滿足實時控制的要求，引入了補償模糊運算元，從而大大提高了收斂速度。
  13. As to large torque ripple in direct torque control ( dtc ) of induction motors at low speed, a kind of new fuzzy neural networks ( fnn ) approach was proposed based on the merits that fuzzy control absorbs man ' s empirical thinking and neural networks have self - organization and self - study ability

    摘要針對異步電動機直接轉矩控制低速轉矩脈動大的間題，充分利用模糊控制吸收入的經驗思維，以及神經網路對信息的處理具有自組織、自學習的特點，提出一種新的模糊神經網路控制方法。
  14. ( 5 ) based on fuzzy control theory, fuzzy neural network ( fnn ) controller is introduced ; the changeable area and hierarchical genetic algorithm is used to training fuzzy neural network. simulation indicated that this designed fuzzy neural controller is effective

    （ 5 ）在模糊控制的基礎上，提出了模糊神經網路控制器，並用本文提出的變區域多層遺傳演算法與bp相結合進行網路學習，在理論上證明了遺傳學習演算法的收斂性。
  15. Fnn efficiently maps the complex non - linear relationship of training data for its automatic learning, generation and fuzzy logic inference

    模糊神經網路具有很強的自學習、泛化和模糊邏輯推理功能，可以有效地映射出訓練數據之間復雜的非線性關系。
  16. Arithmetic of interpolation based on a fnn

    前向神經網路實現的插值演算法
  17. And a guiding mechanism in fnn combines case - reasoning and rule - reasoning powerfully. the adoption of multi - pattern diagnosis and their inner integration reach our diagnosis expectation of integrating system

    模糊神經網路的引導機制把基於實例與基於規則推理有力地結合在一起，系統集成多種診斷模式，並從內部診斷推理機制上相融合，達到系統集成診斷的目的。
  18. Using this fnn decision model, the marine maintenance manager can improve the scientificity of maintenance management, lessen the influence of man induced factors, and it has much practical value. 3

    經過訓練后得到的決策模型，可以提高維修決策的準確性、科學性，減少人為主觀因素的影響，因此有較強的實用價值； 3
  19. The input of fnn is flux linkage and phase current, the output of fnn is rotor position. the fnn is trained off line with the genetic algorithm

    網路採用離線的方式學習，為了滿足系統的實時性要求，網路的離線學習和在線運行都採用遺傳演算法對網路的參數進行調整。
  20. The structure of fuzzy neural network ( fnn ) is decided by the fuzzy rules. furthermore, fnn can be used to fit the smooth curves perfectly

    而模糊神經網路（ fnn ）一旦給定模糊規則，其網路結構就固定，而且模糊神經網路能極為準確的擬合光滑數據曲線。
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