fuzzy rule 中文意思是什麼

fuzzy rule 解釋
模糊規則
  • fuzzy : adj. 1. 有茸毛的，覆著細毛的，如茸毛的。2. 不清楚的。fuzziness n.
  • rule : n 1 規則，規定；法則，定律；章程，規章；標準；（教會等的）教規，條例，教條；常例，慣例。2 統治，...
  1. Then, the antecedence and consequence of a fuzzy rule are referred to as a combination of linguistic values and the corresponding utility of the antecedent part, respectively

    此外，產品的意義並?限定為實物，而是廣泛的解釋為一?可被評估之對象。
  2. 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。
  3. A novel dynamic evolutionary clustering algorithm ( deca ) is proposed in this paper to overcome the shortcomings of fuzzy modeling method based on general clustering algorithms that fuzzy rule number should be determined beforehand. deca searches for the optimal cluster number by using the improved genetic techniques to optimize string lengths of chromosomes ; at the same time, the convergence of clustering center parameters is expedited with the help of fuzzy c - means ( fcm ) algorithm. moreover, by introducing memory function and vaccine inoculation mechanism of immune system, at the same time, deca can converge to the optimal solution rapidly and stably. the proper fuzzy rule number and exact premise parameters are obtained simultaneously when using this efficient deca to identify fuzzy models. the effectiveness of the proposed fuzzy modeling method based on deca is demonstrated by simulation examples, and the accurate non - linear fuzzy models can be obtained when the method is applied to the thermal processes

    針對模糊聚類演算法不適應復雜環境的問題，提出了一種新的動態進化聚類演算法，克服了傳統模糊聚類建模演算法須事先確定規則數的缺陷.通過改進的遺傳策略來優化染色體長度，實現對聚類個數進行全局尋優;利用fcm演算法加快聚類中心參數的收斂;並引入免疫系統的記憶功能和疫苗接種機理，使演算法能快速穩定地收斂到最優解.利用這種高效的動態聚類演算法辨識模糊模型，可同時得到合適的模糊規則數和準確的前提參數，將其應用於控制過程可獲得高精度的非線性模糊模型
  4. This paper brings out a new approach that adopts the fuzzy - rule based technique to detect the syn flooding attacks

    本文提出一種基於模糊邏輯規則檢測出syn湮沒（ synflooding ）攻擊的方法。
  5. The main advantage of rough sets data analysis is that it does n ' t require any prior or additional knowledge about the data, which is then used in this paper to analysis the database, acquiring automatically the hierarchical rule sets. in order to ensure maximum consistency of the quantiflcational data, the genetic algorithms is used to get the optimal number and points of division of quantification intervals. at the same time the quantification intervals is fuzzified and crisp rule sets are then transformed to fuzzy rule sets

    粗糙集數據分析的主要優點在於它不要求任何關于被處理數據的先驗或額外的知識，本文利用其對數據庫進行分析計算，自動獲取數據庫在各個層次上的規則集：在保證量化后的數據庫具有最大一致性的前提下，利用遺傳演算法求取連續屬性值的最優量化區間個數及各個區間分點值；同時將量化區間進行模糊化，將多層次清晰規則集轉化為模糊規則集，利用模糊推理進行決策以提高魯棒性。
  6. Fuzzy system lacks self - study ability and its membership functions and fuzzy rule are chosen by experts subjectivity, and input / output relation obtained by neural network can not be expressed in acceptable way and exists the quality of absoluteness, all of which make diagnosis result not live up to the fact

    模糊系統缺乏自學習能力，隸屬度函數和模糊規則的選取帶有一定的主觀性且依賴于專家；神經網路所獲得的輸入輸出關系無法用容易被人接受的方式表示出來，存在非此即彼的絕對性，使診斷結果與實際情況不符。
  7. To transform a voltage - control problem to a current - control problem, a current - controlled voltage - source inverter ( cc - vsl ) is considered, and a power flow controller based on ph control algoritltnm is designed to improve dynamics of control system and implement closed - loop control to active and reactive power. to promote adaptation and robust, a self - tuned p1 power controller based on fuzzy rule is presented

    論文還探討了採用電流跟蹤控制pwm電壓型逆變器實現sssc的問題，將注入串聯電壓控制問題轉換為逆變器的電流控制問題，以此建立了sssc控制系統的結構，並設計了基於pi控制演算法的sssc的潮流控制器，模擬表明其改善了系統動態特性，實現了對p和q的閉環控制。
  8. ( 6 ) analyzing issues of modeling fuzzy rule - based systems and fuzzy reasoning based existing fuzzy petri net models

    （ 6 ）分析了已有模糊petri網模型在建模模糊產生式系統和模糊推理方面存在的問題。
  9. So, being used the traditional control method, the static and dynamic output is not very satisfied. this paper adopts a fuzzy rule self - adjust control method to the need of industrial constant temperature control

    在復雜的工業控制中，被控對象通常具有嚴重的非線性、時變性以及存在種類繁多的干擾，在採用常規的控制方法，難以獲得滿意的靜、動態性能。
  10. Some methods, such as adding integrator ; making use of neural network to remember fuzzy rule ; utilizing bang - bang controller and adjusting scale and proportion factors online, are researched to modify normal fuzzy controller for optimizing srd ' s dynamic and static performance. the simulation results given in this paper show the srd with modified fuzzy controller has excellent performance

    本文以提高srd動、靜態性能為指標，研究了如下幾種改進模糊控制的方法： （ 1 ）串聯或並聯積分器以提高靜態精度； （ 2 ）利用神經網路記憶模糊控制規則； （ 3 ） bang - bang控制與模糊控制結合； （ 4 ）在線調整量化因子與比例因子。
  11. A fuzzy rule tab is formed. in hardware design, choicing 16 bit single - chip computer. designing singal input circuit. output driving circuit, power source circuit and forming an abs fuzzy control circuit. at last, linking the wheel modelling by virtue of 5196 simulation, experiment sesults ar e given

    在硬體設計方面，根據系統選擇了16位單片機，設計出信號輸入迴路、輸出驅動迴路、電源部分，形成控制器電路圖並製成防抱死制動控制器，最後用串口通訊與雙輪車輛模型連接。
  12. After briefly introduce the basic genetic algorithm ( ga ) theory, aimming at the " prematurity " of basic genetic algorithm, we put forward a new improved genetic algorithm, the basic genetic algorithm combine simulate anneal ing ( gasa ), to meliorate the local search ability of basic genetic algorithm. because many design problems, such as the preliminary fuzzy rule and input and output membership fuction are hard to gain and the learni ng process of fuzzy neural network ( fnn ) is slow and local optimization, we design the fuzzy neural network excitation controllers of turbine generators with genetic algorithm combine simulate anneal ing ( gasa )

    本文首先介紹了水輪發電機勵磁控制方式和軟計算理論的發展，然後介紹了遺傳演算法的基本理論，針對基本遺傳演算法存在的「早熟」現象，介紹了一種遺傳演算法結合模擬退火的改進型遺傳演算法，改善了基本遺傳演算法的局部搜索能力。鑒于常規模糊神經神經網路勵磁控制器設計方法中存在著初始模糊規則和輸入輸出隸屬度函數難以確定以及模糊神經網路訓練緩慢和難以達到全局最優等問題，利用遺傳演算法結合模擬退火的改進型遺傳演算法來設計模糊神經網路勵磁控制器。
  13. Analysis of the fuzzy rule function and limiting structure of typical fuzzy controllers

    典型模糊控制器的模糊規則函數與極限結構分析
  14. Improvement on the method for compressing the fuzzy rule base in fuzzy controllers with the singular value decomposition

    模糊控制器中用奇異值分解法壓縮模糊規則庫方法的改進
  15. The main aim of the proposed fuzzy rule - based method is to develop a useful decision making tool by discovering simplified fuzzy if - then rules, whose consequent part is a real number, from numerical data by using the proposed data mining technique based on genetic algorithm to automatically determine several pre - specified parameters

    本文的主要目的在於發展一有用之決策分析工具，使決策者可應用前述之資訊以制定適當之?銷或經營策? ，而在做法上系發展以基因演演算法為基礎之資?探勘技術，決定一些使用者難以設定之? ? ，以自所收集之資?中找出前?部與后?部分別為語意值組合與該組合相對應之消費者效用之簡化模糊規則。
  16. A mathematical model and its simulation model of fuzzy control based on wheel acceleration and deceleration logic threshold control are presented. a concept of reference velocity is introduced, and a fuzzy rule control table is established

    建立基於車輪加減速度門限值的abs模糊控制器的數學模型和模糊控制模擬模型，給出參考車速概念和模糊控制規則表，並對takagisugeno推理的abs模糊控制系統進行了模擬。
  17. At last, a novel hybrid neural fuzzy inference system is presented. only based on the desired input - output data pairs, both knowledge acquisition and initial fuzzy rule sets are available

    最後，設計了一種新型混合神經模糊邏輯推理系統，該系統僅從輸入輸出樣本數據集即可達到獲取知識、確定模糊初始規則基的目的。
  18. Using maximum - minimum rule to integrate the matrix of fuzzy rule and the matrix of fuzzy input to obtain the fuzzy output

    按最大?最小規則對模糊集合矩陣和模糊規則矩陣進行合成得到模糊輸出。
  19. First fuzzy the evaluating obtained in different ways to get the matrix of fuzzy collection and then get the fuzzy rule according to knowledge and experience

    首先對各分項評分進行「模糊化」形成輸入量的模糊集合矩陣。然後根據知識和經驗確定模糊規則並形成模糊規則矩陣。
  20. T - s model is a novel fuzzy reasoning model which replaces the parameters of traditional reasoning system with linear partial equation. therefore, it can generate complicated nonlinear equation with fewer fuzzy rules. but the conclusional parameter is not a fuzzy rule but a linear equation, it can not be got from expert ' s experience and operational data directly. we must refine the parameter with some algorithm. by constructing t - s fuzzy neural networks we can solve the problem easily

    T - s模型是一種新穎的模糊推理模型，它以線性局域方程取代了一般推理過程中的常數，因此可以用少量的模糊規則生成較復雜的非線性函數。但是由於結論參數是線性函數而非模糊數，所以規則不能直接從專家經驗和操作數據中直接得到，必須通過一定的演算法進行提煉。因此模型參數的辨識成為建立t - s型模糊系統的主要問題。
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