適應度 的英文怎麼說
中文拼音 [shìyīngdù]
適應度
英文
fitness-
The definition of model fitness considers fully the accuracy and complicacy factors, and can get a trade - off identification solution
關于模型適應度的定義，綜合考慮了精確性和復雜性因素，能夠獲取一種比較折中的辨識結果。Taking gobang as an example, this paper proposes the base scheme for solve game problem by adopting the notion of genetic algorithms instead of search tree, and makes some exploratory work on the design of fitness function, it also provides with requirements for designing fitness function
以五子棋為例，提出了用遺傳演算法代替搜索樹法解決博弈問題的基本方案，並對適應度函數的設計作了一些有益地探索，給出了設計適應度函數應滿足的必要條件。Genetic algorithm is used to find arrangement information after first phase matching. rough match result of one arrangement is used as its fitness value in the paper
第一個階段匹配后，本文使用遺傳演算法尋找圖像序列位置關系，該遺傳演算法使用粗略匹配得到的結果作為一種位置關系的適應度。The method combining local ga with global ga optimizes the performance of visual servoing system. first, target recognition preprocess is carried out by global ga. after the fitness value reaches a certain threshold value, the global ga will
主要通過全局ga完成目標檢測的預處理，當適應度值達到一定的閩值以後，它將切換到局部ga來進行一個更為精細的和快速的目標識別。Based on natural selection, it executes three same and simple genetic operators : selection, crossover and mutation. under the leading of fitness value, it makes an efficient searching in complex spaces until acquiring the best result
它基於自然選擇的原理，通過循環執行相同的、簡單的選擇、雜交和變異三種遺傳操作，並在適應度函數值的引導下對復雜的解空間進行有效地搜索，直到獲得最優的解。Finally, simulation experiments, the different parameters set out under the track, population size of the different fitness value of statistical analysis, the results showed that use of genetic algorithms in robot path planning is effective and feasible
最後通過模擬實驗，對不同參數設置下規劃出的路徑進行比較，不同種群大小的適應度值進行統計分析，結果表明，遺傳演算法應用在機器人路徑規劃中是有效的，可行的。It is applicable to various structural distribution networks. while resolving the " large area restoration ", the genetic algorithm execute three same and simple genetic operators : selection, crossing and mutating. it make a self - adaptable and probability overall searching under the leading of fitness value in the whole searching scale until acquiring the best result
在求解網路故障后重構問題時，互動式模糊遺傳演算法通過循環執行相同的、極其簡單的選擇、雜交和變異三種遺傳操作，並在適應度函數值的引導下在搜索空間進行自適應概率性全局搜索，直至獲得全局最優解。In order to satisfy dynamic characteristics of the robot system, the individual that has the maximum fitness value is assigned to be input of the robot visual controller by evaluating inverse kinematics after each generation ga evolution. so the path planning based on ga process is considered to be in real time mode, which satisfies the requirements of a real time dynamic system
為了滿足機器人視覺伺服系統的動態特性，把每一代ga進化后適應度值最大的個體作為機器人視覺控制器的輸入（要通過解機器人逆運動學） ，這樣就可以把基於6a的路徑規劃（目標搜索）看成是實時的，使改進后的ga能夠滿足實時系統的要求。In order to calculate difficult transportation cost between plants and distribution centers in the fitness value function, flow prediction algorithm was presented to find an minimum - cost flow patterns on an network composed of plants, consolidation centers and distribution centers with concave transportation costs and to obtain the appropriate fitness value
為了解決適應度函數中的工廠與分銷中心之間的運輸成本計算困難的問題，提出了流預測演算法，用於確定產品在工廠、集貨中心和分銷中心構成的凹費用流網路中的最優運輸路徑，進而獲得適應度函數值。In this text, we first do some research on the genetic algorithm about clustering, discuss about the way of coding and the construction of fitness function, analyze the influence that different genetic manipulation do to the effect of cluster algorithm. then analyze and research on the way that select the initial value in the k - means algorithm, we propose a mix clustering algorithm to improve the k - means algorithm by using genetic algorithm. first we use k - learning genetic algorithm to identify the number of the clusters, then use the clustering result of the genetic clustering algorithm as the initial cluster center of k - means clustering. these two steps are finished based on small database which equably sampling from the whole database, now we have known the number of the clusters and initial cluster center, finally we use k - means algorithm to finish the clustering on the whole database. because genetic algorithm search for the best solution by simulating the process of evolution, the most distinct trait of the algorithm is connotative parallelism and the ability to take advantage of the global information, so the algorithm take on strong steadiness, avoid getting into the local
本文首先對聚類分析的遺傳演算法進行了研究，討論了聚類問題的編碼方式和適應度函數的構造方案與計算方法，分析了不同遺傳操作對聚類演算法的性能和聚類效果的影響意義。然後對k - means演算法中初值的選取方法進行了分析和研究，提出了一種基於遺傳演算法的k - means聚類改進（混合聚類演算法） ，在基於均勻采樣的小樣本集上用k值學習遺傳演算法確定聚類數k ，用遺傳聚類演算法的聚類結果作為k - means聚類的初始聚類中心，最後在已知初始聚類數和初始聚類中心的情況下用k - means演算法對完整數據集進行聚類。由於遺傳演算法是一種通過模擬自然進化過程搜索最優解的方法，其顯著特點是隱含并行性和對全局信息的有效利用的能力，所以新的改進演算法具有較強的穩健性，可避免陷入局部最優，大大提高聚類效果。Firstly, in this thesis, we discuss the development of one - dimensional cutting stock problems and other well - known algorithms about them, summarize the basic principle of genetic algorithms, and analyze the effect of coding, fitness function, crossover operators and mutation operators in the genetic process of genetic algorithms
本文首先介紹了一維下料問題的研究概況及其已有的著名演算法，綜述了遺傳演算法的基本原理和方法，分析了遺傳演算法的編碼、適應度函數、交叉和變異運算元在整個遺傳演算法的運算過程中的作用。So, optimization of breakwater planning is of great practical value and should be resolved immediately. at first, the paper narrates the development of numerical modeling, which includes shallow water dynamics theory and method, and compares the boussinesq model and mild - slope equation model. the purpose is to select one model that best fit for wave calculation in harbor engineering
本文首先綜述了波浪數值模擬的發展概況，其中包括淺水動力學的常用理論和方法，並詳細比較了目前使用較多的boussinesq模型和緩坡方程模型，其目的是選擇其中較為適合港區工程波浪計算的模式，並將其作為優化模型的驗證或用於適應度計算。For the job - shop problem, the operator selecting and algorithm realization based on working procedure coding and based on job coding is investigated in the paper. some key algorithm such as fitness evaluation function is given in detail. genetic algorithm is employed to search for the optimized parameters of pid controller applied to ship controling
對于作業車間調度問題，本文分別探討了基於工序編碼和基於工件編碼的調度問題的運算元選擇和演算法實現，對于關鍵演算法如適應度評價函數的實現進行了詳細的討論，並給出了具體的實現步驟。The peony pavilion of a play classic has various chinese and foreign editions, fulfilling to accept the esthetic literary history theories that readers get involved ins this paper regards accepting the esthetic methodology as the degree of dimension for bai xian - yong the peony pavilion plans, investigates to deduce from literature classic to the drama process, investigates the reader ' s baixian - yong arriveing at the white that is used as the fabricator of the conversion, and investigates the western and modern theories on the chinese classic that a play reorganizes
文章以接受美學方法論為維度，就白先勇《牡丹亭》的策劃、製作和傳播進行縷析，探索從文學經典到戲劇演繹的接受歷程，探索作為讀者的白先勇到作者的白先勇身份轉換，探索西方現代理論對中國古典名劇改編的適應度。Firstly, we introduced the main idea, the formalized description, and the basic flow of co - evolution algorithm. then, from the point of pattern analyzation, we established the mathematics model of the multi - population co - evolution algorithm based on pattern replicator equation of the single population genetic algorithm, and made the theoretical analysis and compare for the method of best choice and the method of random choice of the co - evolution algorithm. we put forward a new method for the individual fitness evaluation, and validated the performance of the new method by the simulation experiment
首先，在介紹了協進化演算法的核心思想、形式化描述和基本演算法流程的基礎上，從模式分析角度出發，建立了基於模式復制方程的多群體協進化演算法數學模型，對協進化演算法中的最優選擇法和隨機選擇法進行了理論分析與比較，提出了一種新的個體適應度評價方法，並通過模擬實驗驗證了新方法的效率。On the other hand the information cryptogram technology and card identification of 1c appl ication system are also introduced. a novel fingerprint image preprocessing method is studied based on the trend of fingerprint veins, and some feature extraction and fingerprint matching methods based on fingerprint minutia based on a novel multi - fitness genetic algorithm ( mfga ) are also studied
在分析了國內外指紋識別理論研究的基礎上，研究了一種基於指紋紋線趨勢的指紋圖象預處理方法並取得了較好的模擬效果；研究了遺傳演算法在指紋模式匹配中的應用，針對遺傳演算法在模式匹配的局限性，提出了一種多適應度遺傳演算法（ mfga ） ，並在此基礎上對原遺傳匹配演算法做了進一步的改進。Its encoding way is also analyzed in this paper. we adopt sa to produce the initial packing, which ensure the parent generations are choiceness. the crossover ( pc ) can prevent the fitness individual to be abandoned, the probability of mutation ( pm ) can prevent the algorithm is convergent before premature
文中對其編碼方式進行分析，採用模擬退火法產生初始布局，保證了父輩解群的優良性，採用交叉概率pc有效地防止具有高適應度值的個體被排擠掉，變異概率pm防止了搜索在成熟前收斂。It bases on the evaluation of adaptability, and uses probability searching technology to find out the problem ’ s satisfying solution
它基於適應度評價，並使用概率搜索技術，找到問題的滿意解。Based on the genetic algorithm ' s global searching capability with probability regulation and euclid ' s space distance metric to settle multi - objective, the algorithm that integrates multi - objective ' s decision - making into the modified genetic algorithm to solute the optimal model with discrete variables and multi - objective is proposed. during the algorithm ' s design, the euclid ' s space distance metric is proposed to transform the multi - objective problem into single objective problem. and some modified measure to fitness function and crossover probability and mutation probability are used to improve the performance of the algorithm and avoid premature convergence
演算法設計過程中，利用歐幾里德空間距離準則和罰函數法，將含有約束條件的多目標規劃問題轉化為無約束的單目標優化問題；針對簡單遺傳演算法出現的早熟，構造隨進化代數動態調整適應度的適應度函數和隨個體適應度自適應調整的交叉、變異概率；提出比例選擇與精英保留策略相結合的選擇、兩點交叉和簡單變異的改進遺傳演算法。Better segmentation effect can be attained by coding gray levels of pixels as eigenvector, taking advantage of histogram entropy principles function as fitness function, adopting ranking selection operation, making use of arithmetic crossover and mutation at a certain probability, combining with clustering analysis to initialize clustering center of the population to segment cells image with genetic algorithm
以像素的灰度值為特徵向量進行編碼，利用直方圖熵法準則函數作為適應度函數，採用基於排名的選擇操作，以一定的概率進行算術交叉和變異，並結合聚類分析設定種群的聚類中心對細胞圖像進行遺傳聚類分割。分享友人