最優遺傳系統 的英文怎麼說

中文拼音 [zuìyōuyízhuànxìtǒng]
最優遺傳系統 英文
optimum genetic system
  • 最 : 副詞（表示某種屬性超過所有同類的人或事物） most; best; worst; first; very; least; above all; -est
  • 遺 : 遺動詞[書面語] （贈與） offer as a gift; make a present of sth : 遺之千金 present sb with a gener...
  • 傳 : 傳名詞1 （解釋經文的著作） commentaries on classics 2 （傳記） biography 3 （敘述歷史故事的作品）...
  • 系 : 系動詞（打結; 扣） tie; fasten; do up; button up
  • 統 : Ⅰ名詞1 （事物間連續的關系） interconnected system 2 （衣服等的筒狀部分） any tube shaped part of ...
  • 最優 : optimal; optimum最優策略 optimal policy; optimal strategy; 最優設計 optimum design; 最優值 optima...
  • 遺傳 : [生物學] heredity; hereditary; inheritance; inherit
  • 系統 : 1. （按一定關系組成的同類事物） system 2. （有條理的;有系統的） systematic
  1. The method proposed in this thesis do well in solving the problems of multi - damping - ratio - spectra simulation. it is convenient to obtain the pareto optimal solution set of the multi - object question by using implicit parallel genetic algorithms and the method can meet the practical needs for simulating ground motions coinciding with multi - damping - ratio - spectra in seismic design. the crossing rate and variance rate are important parameters of genetic algorithms which affect the rate of convergence, the adapting rate of cross and variation in this paper can auto - adapt and according to stand or fall of current sample, it assures the sample approach to the pareto optimal solution set in fast convergent speed

    較好地解決多阻尼比反應譜擬合問題；本文方法通過一次運行就能獲得一組具有集系特性的地震動，在擬合多阻尼比反應譜的人造地震波集系的模擬方面有傳統方法所不能比擬的優勢，產生的人造波或人造波集系可滿足工程抗震設計需要；在遺傳演算法中，交叉概率和變異概率是影響收斂速度的重要參數，本文採用的改進自適應交叉概率和變異概率，可以根據當前樣本的好壞程度來自動地選擇適當的交叉概率和變異概率，以保證演算法始終以較好的速度向pareto最優解集逼近。
  2. A rate - dependent damage evolution modified zwt nonlinear constitutive ralation is adopted, an object function of least square was established according to the experimental results. the searching space of each decision variable was foreordained with conventional optimizing method, and all parameters in zwt model for solidified pf resin were determined with generic algorithms

    基於實驗曲線構建了最小二乘形式的目標函數，並採用傳統優化方法輔助設計了各個決策變量的搜索空間，進而用遺傳演算法確定了損傷型zwt非線性粘彈性本構關系中的材料參數。
  3. Through calculating annual expenses and analyzing investment risk, an optimization model firstly put forward. the coefficient of investment profit of the irrigation system, which includes pipe distribution networks, drop irrigation device, is minimized. the coefficient is optimization design ' s target function which is by the genetic algorithms to solve

    在系統優化方面，單獨作為一個模塊用vc + +實現，本文首次提出了以包括管網、灌水器、水泵、電機等設備在內的微灌系統的益本比最大為目標函數，利用遺傳演算法求解的方法。
  4. We use genetic algorithm ( ga ) to realize agents " coalition formation. ga can reduce the cost of searching the optimal solution or quasi - optimal solution, and enhance the efficiency of the whole system

    本文使用遺傳演算法來實現機器人聯盟形成，遺傳演算法能夠減少尋找最優解或可行解的開銷，從而提高整個系統的效率。
  5. 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
  6. Considering of the differences of task scheduling between a grid and a distributed system, this dissertation designs a real number encoded mode that mapping every task to a random resource directly by improving the encoding mode of the traditional genetic algorithm, and gives a particular design to the encoding and decoding mode. at last, this algorithm is simulated in the grid simulator. the experiment results show that the reformative genetic algorithm not only has a holistic searching ability, but also makes a fast convergent speed, which provides a preferable performance

    本文根據網格計算任務調度的特點，提出了基於改進的遺傳演算法的網格任務調度，通過對傳統遺傳演算法的編碼方式進行改進，針對網格任務調度與一般分散式系統任務調度的不同之處，設計了資源?任務的一一對應的實數編碼方法，詳細設計了其編碼及解碼方式，最後在網格模擬器中進行了模擬，實驗數據證明了改進后的遺傳演算法即具有全局搜索能力，又具有較快的收斂速度，具有較好的性能，該實驗達到了本文以實現任務調度的最優跨度為目標的實驗目的。
  7. It is very important to estimate the basic parameters in helicopter preliminary design. neural network ( nn ) has the advantages in estimating accuracy and generalization over traditional methods. however, there are some difficulties in using nn, e. g., how to select a proper network structure and the number of hidden layers. in this paper, structure and connection weight of a three - layer nn are optimized by genetic algorithm, and the optimized network is applied to helicopter sizing. the proposed method can not only give an optimal nn structure and connection weight, but also reduce the prediction error and has the capability of self - learning when the latest data are available. furthermore, this method can be easily applied to helicopter design systems

    在直升機初步設計階段估算其基本參數是很重要的.神經網路的通用性和精度比傳統的估算方法有更多的優勢，但是在應用神經網路時存在如何選擇合適的網路結構和隱層節點數目等一些困難.應用遺傳演算法優化三層神經網路結構和連接權重，並將優化得到的網路應用於直升機參數選擇中.該方法不但可以給出一個最優的神經網路結構和連接權重，而且降低了估算誤差，具有及時應用最新數據學習的能力.此外，該方法易於在直升機設計系統中得到應用
  8. 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
  9. A niched - penalty approach is used to transform this optimal kinematical design problem to an unconstrained one. a kinematic accuracy comparison of the genetic designed fine - tuning stewart platform with the quasi - newtonian designed one is made. the comparison results have shown that the kinematic accuracy of the genetic designed fine - tuning stewart platform has a much higher accuracy and a compact structure than that of the quasi - newtonian designed one, which guarantees the accomplishment of high precision trajectory tracking and reduces the disturbance of wind to the feed - supporting system

    以並聯機器人jacobian矩陣的條件數為優化設計的目標函數，提出了基於遺傳演算法的並聯機器人最優運動學性能結構參數優化設計方法，採用實值遺傳演算法，對精調stewart平臺進行了優化設計，得到了最優運動學的精調stewart平臺結構參數，為實現新一代大射電望遠鏡饋源指向跟蹤系統高精度軌跡跟蹤控制奠定了堅實的基礎。
  10. Finally, jinduicheng mo. company open - pit is quoted as an instance for building mine transportation vechile scheduling system model, and according to the model, adopt genetic algorithm to study the optimization of mine transportation vechile scheduling system. a rational project is given to this problem, the paper also analysized the optimial design of mine transortation vechile scheduling, the model offering in this paper, convergence of optimal algorithm and data bank management, and transportation project of minerals and disposals is optimized, which realize the decision of transportation project and data visibilization, and wich improves the science and information process of transportation department management

    最後，論文以金堆城鉬業公司露天礦為例建立礦山運輸車輛優化調度模型，結合所建立的礦山車輛優化調度模型，採用遺傳演算法對礦山運輸車輛系統進行優化研究，為其提供合理的體系方案。並對礦山車輛優化調度系統設計進行了詳細分析，提出的礦山車輛優化調度系統，集優化演算法與數據庫管理分析於一體，進行礦巖運輸方案的優化，實現調度方案決策的可視化、運行數據的可視化，促進運輸部門管理的科學化、信息化進程。
  11. According to the shortage of ga converging to a local optimal solution because of reducing the diversity of individuals, the theory of biological immune system is cited, the immune operators including calculation the densities of antibodies, activating or suppressing antibodies and making the memory cell are designed, and effectively combined with ga operators

    同時，針對遺傳演算法在收斂計算後期，由於種群趨向單一化，出現早熟現象而陷入局部最優解的缺點，借鑒生物原理的免疫系統，設計出抗體濃度計算、抗體的抑制/促進、構造記憶單元等多個免疫運算元，並與遺傳運算元進行有效結合。
  12. 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。
  13. 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。
  14. Because the designing fin and oar and the experiment fin and oar pro rata, so we can use the coefficients to calculate our designing fin and oar " s rising force. secondly, constituted the control system of pushing fin, and studied its control scheme. lastly, used matlab to simulate our control system, and applied ga to optimize the parameters of pid controller ; from the simulation result we can see the pushing fin has the ability of reducing the ship shake in all speed

    最後，對推力鰭減搖裝置控制系統用matlab語言進行模擬，並應用遺傳演算法理論，對推力鰭控制系統中的pid控制器參數進行優化，並將模擬效果與傳統的鰭的減搖模擬效果進行對比，從模擬效果上可以看出，推力鰭減搖裝置控制系統的減搖效果在低航速下優于傳統的鰭的減搖效果，而且在中、高航速下推力鰭的減搖效果也能達到傳統鰭的減搖效果，打到了設計的目的。
  15. Based on the discussions of the conventional and recent methods of short term load forecasting such as time series, multiple regression approaches and artificial intelligence technologies, this paper presents a hybrid short term forecasting model which combines the artificial neural network ( ann ) and genetic algorithm ( ga ). in order to improve the convergence speed and precision of the back - propagation ( bp ), a new improved algorithm - the adapted learning algorithm based on quasi - newton method is given

    本文首先分析比較了電力系統短期負荷預測的傳統方法時間序列法和回歸方法以及最近的專家系統和神經網路技術的優點和不足，然後針對人工神經網路bp演算法的不足對其進行了改進，採用了基於擬牛頓的自適應演算法，它提高了網路學習效率，具有較快的收斂速度和較高的精度。接著提出了改進的遺傳演算法來改善神經網路的局部收斂性。
  16. Genetic algorithm is used to optimize the parameters of pid controller that is used to control the plant lon ( local operating network ) is designed to control vav air - conditioning system. by this means the static pressure control and minimum total supply air volume control are experimented. the paper analyzes the coupling among loops, the whole system ' s stability and energy saving effect under the two control methods

    針對目前變風量空調系統的模型都是用機理建模方法建立的情況，本論文用最小二乘法對機組部分進行系統辨識，建立了水閥?送風溫度、變頻風機?靜壓兩個迴路的模型，經驗證比較接近實際系統；採用遺傳演算法對pid控制器的參數進行尋優，尋優結果令人滿意；設計了變風量空調系統的lon控制網路，以此為實現手段，進行了定靜壓控制和最小總送風量控制，並在兩種控制方式下，分析了各個迴路的耦合情況、兩種控制方式的穩定性和節能效果。
  17. To investigate the influencing law of technical elements in enterprise production, based on certain assumptions, a three - element ( technology, labor and capital ) output function is defined ; through conceiving and solving an optimization model under the condition of invariable total production cost and maximum output, this paper deduces the optimal proportioning relationship between optimum technical growth rate and conventional production factors - labor and capital, further constructs the optimization model of technical growth rate under total production cost constraint, and design a genetic algorithms program to solve such model

    摘要為了考察企業生產中技術要素的作用、規律，在一定的假設條件下，對其技術要素下了定義，認為其產出函數包括技術、勞動及資本要素；通過構建與求解生產總成本，構建最大條件下的優化模型，推導出技術最優增長率與傳統生產要素勞動與資本的優化配比關系，進一步構造了企業在生產總成本約束下的技術增長率優化模型，並設計了遺傳演算法程序對模型進行求解。
  18. Facing to manufacturing system, this paper analyzed its characters and evolvement of production management modes, demonstrated that lean production and human - based theory were practical ways to reform our manufacturing systems fit for the reality. a division method was raised to separate the job - scheduling problem into shop and station types, and emphasis was pressed on the study of partheno - genetic algorithm ( pga ), a revised genetic algorithm, to calculate this problem. a new kind of gene joint - move algorithm was also raised

    針對製造系統，分析其生產管理模式的特點和變遷，論證了精益生產和以人為本的思想是適合現階段我國實際的製造系統管理模式改造途徑，對其中的主要具體問題?作業計劃調度提出shop （車間）和station （工作站）型兩分法，求解上重點研究了遺傳演算法的改進型式?單染色體遺傳演算法（ pga ）的基本理論，提出一種基因聯合移位運算元，證明了演算法的有效性與優越性，研究了如何將pga應用於製造系統作業調度這一復雜的組合優化問題，針對生產中總時間最短和jit兩種生產性能指標，給出了具體的解決方案及運算過程。
  19. Finally, according to the variants of fas are much and dependant one another, an human - machine incorporate optimization approach combining domain knowledge with genetic algorithms is proposed to scheduling the flexible assembly system

    最後根據系統設計涉及因素多且相互制約的特點，提出結合領域知識和遺傳演算法的人機一體優化策略對柔性裝配系統進行規劃設計。
  20. The scheduling of a hydrothermal system with a progressive optimal genetic algorithm

    水火電力系統優化調度的逐步最優遺傳演算法
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