fuzzy-genetic system 中文意思是什麼
fuzzy-genetic system
解釋
模糊遺傳系統-
They learn from others " strong points to offset one ' s weakness, therefore two research direction - genetic fuzzy system and fuzzy genetic algorithm ( fga ) - appear
現階段，模糊遺傳演算法的發展還不十分成熟，對其認識也眾說紛紜。 -
2. a method combining some of the composite space structural simulation, wavelet analysis, fuzzy mathematical, genetic algorithm, artificial intelligence, expert system, vibration diagnosis, acoustic sounding, supersonic flaw detection, radioscopy, infra - red detection and so on to diagnose the composite structure damage is discussed
本文對把復合材料大跨建築結構模擬、小波技術、模糊數學、遺傳演算法、人工智慧、專家知識、振動診斷、聲發射技術、超聲波檢測、射線探傷、激光全息檢測、紅外線檢測等方法中的幾種融合在一起對復合材料大跨建築結構進行損傷診斷的方法進行了探討。 -
In study of the submarine movement in deep sea a new approach with fuzzy sliding - mode control and double - gene genetic algorithm is proposed for designing combined maneuvering control system of submarines. simulation results showed that the approach not only remains robustness of sliding - mode control, but also avoids thq effect of chattering phenomenon, possess better performance of the system
在研究潛艇在深海航行的操縱控制中，首次提出了具有雙基因遺傳演算法的模糊滑模控制器的新方法，模擬結果表明了該方法不僅避免了抖振的影響，而且具有很好的系統性能。 -
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 -
Study on intelligent flight control system based on genetic algorithm and fuzzy logic control
基於遺傳演算法和模糊邏輯的智能飛控技術研究 -
A method of fuzzy optimization design based on genetic algorithm is presented as a new method of parameter optimization design for dc double closed loop speed adjusting system. the method covers three steps. firstly, speed overshoot rate and settling time are chosen as performance indice according to the demand of engineering. these indice are normalized by using fuzzy membership function and then weighted to form objective function of optimization model of the system. secondly, the dynamic response curve of the system with corresponding parameters and peoformance indice are obtained by computerized numerical calculation and simulation. finally, parameters of engineering design are expanded as searching space ; and parameters of speed regulator and current regulator are taken as genes in chromosome. these genes in searching space are optimized to get best solution by way of genetic algorithm. as shown by experimental results, the parameters designed by this method are capable of significantly improving performance indice of the system, which proves that it is a practical and effective method
提出一種基於遺傳演算法的直流雙閉環調速系統參數優化設計方法.根據工程技術的要求，選用速度超調量和過渡時間作為參數優化性能指標.將該指標用模糊隸屬度函數歸一化，再加權平均形成系統優化模型的目標函數.採用計算機數值計算方法，通過模擬獲得系統對應參數的動態響應曲線及其性能指標.最後以工程設計的參數為搜索范圍，以速度調節器和電流調節器的參數為染色體中的基因，通過遺傳演算法在搜索范圍中優化這些基因，獲得優化解.實驗結果表明，所設計的參數能使系統性能指標有顯著提高 -
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。 -
In the paper, a speed estimator based on artificial neural network is designed according to the principle of direct torque control, the speed estimator is optimized by genetic algorithm, and the parameters of pid speed adjuster is also optimized by genetic algorithm. a stator linkage and torque observer based on stator resistance estimator using fuzzy neural network is also designed. eventually, the intelligent control of direct torque control system is implemented
本文根據異步電動機直接轉矩控制原理，在應用人工神經網路進行速度辨識的基礎上，利用遺傳演算法對神經網路速度辨識器進行了優化設計；運用遺傳演算法對pid速度調節器的結構和參數進行了整合；在採用模糊神經網路對電機定子電阻辨識的基礎上，進行了定子磁鏈及轉矩的觀測，為最終實現無速度傳感器直接轉矩控制系統的智能控制創造了條件。 -
This paper exhausts fully adjustable factor which could amend the dynamic function in fuzzy control system, and that traditional algorithms select factors with intercession is easy to get a partial solution, so this paper presents a new method to select factors based on genetic algorithm. this method has a large range over covered the solutions which could benefit to search the best solutions. it has great character and advantage
本文充分闡述了可調整因子在模糊控制中能夠改善了系統的動態性能，並根據傳統的優化演算法在選取控制因子時是從單個初始值迭代求取最優解的、很容易陷入局部最優解這一問題，提出了一種基於遺傳演算法的可調整因子的選取方法，這種方法覆蓋面比較大，有利於全局擇優。 -
The stress is basing coal - fired boiler inflammation system feature and control demand to design a kind of fuzzy - pi controller on based of genetic algorithm to control it. the controller refers the error and its variety rate as its inputs. and, in order to make the control qualities much better, concerns them as the performance index to optimize the membership function of the fuzzy variables and the pi ' s controller parameter by means of online adjujsting the genetic algorithm, inflammation system steam pressure loop and economic inflammation loop
重點是針對燃煤鍋爐燃燒系統的特點和控制要求，設計了一種基於遺傳演算法的模糊- pi復合控制器對其進行控制，該控制器以偏差、偏差變化率作為輸入量，通過遺傳演算法在線調整模糊控制器的模糊變量隸屬度函數和pi控制器的參數，從而達到優化模糊控制規則和pi控制器參數的目的，實現燃燒系統的蒸汽壓力迴路和經濟燃燒迴路的控制要求。 -
In order to complete the research on optimal control regular for coal - fired boiler inflammation system. in this paper, a type of coal - fired boiler inflammation system is regarded as the research target, after separately analyzed steam pressure loop and economical inflammation loop, we obtained the relevant control scheme, and designed a kind of fuzzy - pi compound controller on based of genetic algorithm to control two loops, and using genetic algorithm tool kit below the matlab progressed system simulation research
為了完成對燃煤鍋爐燃燒系統的最優控制規律的研究，本文以某型燃煤鍋爐的燃燒系統作為研究對象，分別對其蒸汽壓力迴路和經濟燃燒迴路進行系統分析，得到了相應的控制方案，設計了一種基於遺傳演算法的模糊- pi復合控制器對該系統進行控制，並用matlab下的遺傳演算法工具箱進行了系統模擬研究。 -
Simulation research of naval ships refrigerator fuzzy control system based on genetic algorithm
基於遺傳演算法的船艇冷庫模糊控制模擬研究 -
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。 -
Real time optimization research and application of mining scheduling system based on genetic algorithms and adaptive network fuzzy inference system
的露天礦山開采調度系統的實時優化與實踐 -
Fuzzy genetic algorithm - based electro - hydraulic servo system control
基於模糊遺傳演算法的電液位置伺服系統控制 -
2 utilize matlab simulating optimization design for first - order system with large time - delay and compare their results with the system designed by pid. 3 design the hardware system and software system of the fuzzy intelligence inverter air - conditioner based on genetic algorithms
2 、利用matlab軟體對基於遺傳演算法模糊智能空調控制系統進行模擬，中文摘要基十遺傳演算法模糊智能變頻空調機理的研究並與模糊邏輯控制演算法、 pid演算法模擬進行對比研究。 -
In this thesis 2 - dimension fuzzy - control system with adjustable factors was analyzed and simulated using matlab as tool of data processing. genetic algorithm was used to search for the best adjustable factors
本論文用matlab作為數據處理工具，分析和模擬帶可調整因子的二維模糊控制系統；用遺傳演算法作為尋優演算法搜索最佳可調整因子。 -
After training the neural network and fuzzy inference system with the method named gauss newton levenberg - marquard, we optimize these two systems with chaotic optimization method. simulated annealing algorithm and genetic algorithm can find the better solution, with the help of chaotic optimization method
提出高斯牛頓levenberg ? manquardt方法和混沌優化相結合的演算法，利用該方法對神經網路和模糊神經網路進行了訓練，並用混沌進行了優化；還和模擬退火、遺傳演算法進行了結西安理工大學碩士論文合，幫助它們找到更好的解。 -
In the dissertation, the genetic algorithm is employed to combine with fuzzy control to design and implement the autopilot control system. the ga is used to optimize the parameters of fuzzy control system. the following simulations show that the fuzzy autopilot control system optimized by ga has higher control accuracy, better robustness and resistant disturbance capability
本文引入了遺傳演算法與模糊控制相結合的控制方法實現了潛艇自動舵系統的設計和實現，採用遺傳演算法優化控制參數后模糊控制系統與單一的模糊控制系統分別進行模擬，其結果表明，優化后的控制系統對于外界參數的改變能夠達到控制的目的，提高控制的精度，基於模糊控制和遺傳演算法的自動舵顯示了更好的魯棒性和抗干擾能力。 -
In the simulation of functions, this method performs better than chaotic optimization algorithm. with the combination of bisection - interpolation approach and gauss newton levenberg - marquardt method, we optimize neural network and fuzzy inference system. taking advantage of bisection - interpolation approach, simulated annealing algorithm and genetic algorithm find the better solution than chaotic combination method
作者通過大量的函數模擬以及將其與牛頓高斯levenberg一manquardt方法、模擬退火、遺傳演算法等常用演算法相結合，形成的混合優化演算法，對神經網路、模糊神經網路和函數進行了優化，其優化效果明顯優于混飩以及混飩混合優化演算法。
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