適應性搜索法 的英文怎麼說

中文拼音 [shìyīngxìngsōusuǒfǎ]
適應性搜索法 英文
adaptive search
  • 適 : 形容詞1 （適合） fit; suitable; proper 2 （恰好） right; opportune 3 （舒服） comfortable; well Ⅱ...
  • 應 : 應動詞1 （回答） answer; respond to; echo 2 （滿足要求） comply with; grant 3 （順應; 適應） suit...
  • 性 : Ⅰ名詞1 （性格） nature; character; disposition 2 （性能; 性質） property; quality 3 （性別） sex ...
  • 搜 : 動詞1. （尋找） collect; gather2. （搜查） search; ransack
  • 索 : Ⅰ名詞1 （大繩子; 大鏈子） a large rope 2 （姓氏） a surname Ⅱ動詞1 （搜尋; 尋找） search 2 （要; ...
  • 法 : Ⅰ名詞1 （由國家制定或認可的行為規則的總稱） law 2 （方法; 方式） way; method; mode; means 3 （標...
  • 適應性 : adaptability; flexibility
  • 適應 : suit; adapt; get with it; fit
  • 搜索 : 1 （仔細尋找） search for; ferret about; hunt for; scout around 2 [電子學] hunting; scan; [控] in...
  1. Edm has some remarkable advantages over traditional models, includes using implicit causal models, self - learning capacity, weak dependence on domain knowledge, wide applicability, robustness, self - adaptability, and population - based searching, etc. tracing back its intrinsical ideas, edm is just making use of the nature ' s decision making strategy, natural selection, to solve the decision making problems faced by human or the intelligent agents

    進化決策主要利用了進化演算法與形式化計算模型相結合所具備的自動建模能力，它具有隱式因果模型、自學習、弱知識依賴、應用廣泛、穩健性、自適應和群體搜索等優勢。追根溯源，進化決策的基本思想正是利用大自然的決策機制（自然選擇）來解決客觀世界所提出的決策問題，而自然進化又是已知的能力最強的問題求解范型。
  2. 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。
  3. 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。
  4. Considering the one - sidedness and inaccuracy of knowledge discovery only from single - color database, an approach is proposed to discover knowledge from 1331 groups of mix - color database with partial least - square regression, based on measuring and learning 400 groups of single - color database. by this method, the mean error decreases when converting from rgb to cmyk, the precision of color matching is improved, and the automatic and general problem in color matching is further solved

    本文基於統計學習理論構造了一種快速自適應隨機搜索演算法，證明了演算法的收斂性.給出了一種簡易實用的寬帶天線匹配設計新方法.應用該自適應演算法進行天線匹配設計，不僅演算法簡單，易於編程實現;而且能夠快速設計出具有較好性能的匹配網路，非常適用於各種短波、超短波天線的匹配設計問題
  5. Genetic algorithm, as a computational model simulating the biological evolution process of the genetic selection theory of dar - win, is a whole new global optimization algorithm and is widely used in many fields with its remarkable characteristic of simplicity, commonability, stability, suitability for parallel processing, high - efficiency, and practibility. on the other hand, there are many op - timization problems in the field of digital image processing, such as image compression, pattern - recognition, image rectification, image segmentation, 3d image recovery, image inquiry, and or so. in fact all these problems can be generalized as the problem of searching for a global optimal solution in a large solution space, which is the classic application field of genetic algorithm

    遺傳演算法是模擬達爾文的遺傳選擇和自然淘汰的生物進化過程的計算模型，是一種新的全局優化搜索演算法，具有簡單通用、穩定性強、適于并行處理以及高效、實用等顯著特點，在很多領域得到了廣泛應用，另一方面，在圖像處理領域有很多優化問題如圖像壓縮，模式識別，圖像校準，圖像分割，三維重建，圖像檢索等等，實際上都等同於一個大范圍搜索尋優問題，而最優化問題是遺傳演算法經典應用領域，因此遺傳演算法完全勝任在圖像處理中優化方面的計算。
  6. Adaptive mutation algorithm has been adopted to ensure the global random searching speciality for feasible individual

    而對可行個體，則採用自適應變異演算法，以保證演算法的全局性隨機搜索特性。
  7. Then we go to details of the ideas of compression algorithms based on ifs theory, such as range block search, fixed threshold, adaptive threshold, linear classification, and so on

    這些演算法包括：全局分塊搜索演算法、固定門限法、自適應門限法、線性分類法、四分之一塊灰度排列法和基於塊合併的壓縮演算法。
  8. 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。
  9. The self - tuning algorithm of the parameter adopts eigenvalue of the systemic error and derivative error and so on. thus this method can overcome the disadvantage of the previous method which make the calibrating date not match up to the moveable track of the system, and improve the adaptability, rapidity and robustness of the human simulating intelligent control ' s algorithm

    該方法將誤差、誤差導數等特徵量引入參數在線校正公式，克服了以往採用盲目搜索法時校正量與系統實際運行軌跡不匹配的缺點，提高了仿人智能演算法的適應性，快速性和魯棒性。
  10. In this thesis, we improve viterbi beam search algorithm from tow aspects. on the one side, we present a new adaptive viterbi beam search algorithm referred to as adaptive viterbi beam search algorithm based on variation of active model numbers

    一方面，使用自適應的裁剪門限代替固定不變的裁剪門限，分析了現有自適應viterbibeam搜索演算法的局限性，提出了基於活動模型數變化的自適應viterbibeam搜索演算法。
  11. In this paper ， an optimal search strategy by dividing the whole surveillance area into regions is presented so that the optimal search can be adaptively implemented in phased array radar. firstly ， the inherent relationship among average discovering time ， radar resources consumption ， search frame period and target distribution density is studied. secondly ， parameters for the region search are optimized to achieve the optimal search performance inside regions. then ， the optimal search frame period for each region is derived to minimize the average discovering time of targets ， where the constraint of radar time resource and the importance of each region are taken into account. finally ， the adaptability of this search strategy is discussed. only if the optimal parameters for each region are utilized and the beams are scheduled according to the optimal frame period under the radar time constraint ， the optimal distribution and the optimal scanning sequence of beams can be implemented adaptively. thus ， optimal search is adaptively implemented in the whole surveillance area

    本文提出一種分區搜索演算法，實現了相控陣雷達的自適應最優搜索.首先，研究了各區域平均發現一個目標消耗的雷達資源和目標被發現的平均時間同搜索幀周期以及目標強度的關系；然後，研究了在各區域採用兩步搜索演算法的最優參數設計，實現了局部區域的最優搜索；其次，在雷達時間資源有限和區域重要性加權的約束條件下，導出了使目標被發現的平均時間最小的區域最優幀周期；最後，討論了分區搜索演算法的自適應性.只要採用各區域的最優參數，按最優幀周期調度雷達波束，就可以自適應地實現使目標被發現的平均時間最短的波束的最優分佈和掃描順序，即自適應最優搜索
  12. Reactive tabu search algorithm for time - dependent vehicle routing problem with backhauls

    適應性禁忌搜索演算法求解帶回程的時變速度車輛路徑問題
  13. Genetic algorithm is a kind of stochastic whole - searching regression algorithm, which is built on natural selection and molecule genetic mechanism, as a kind of universal algorithm to optimize the problems of complicated system, it is widely used in many fields due to its suppleness, universality, well self - fitness, robustness and fitness for collateral process, as a kind of bionic algorithms, the research on ga ' s application keeps far ahead of its theoretic research

    遺傳演算法是藉助生物界自然選擇和遺傳學機理而建立的一種迭代全局優化隨機搜索演算法，是一種求解復雜系統優化問題的通用框架。它不依賴于問題的具體領域，具有簡單、通用、較強的自適應性和魯棒性，以及適于并行處理等顯著特點，因此被廣泛應用於眾多領域。作為一種仿生演算法，遺傳演算法的應用研究遠遠領先於演算法的基礎理論研究。
  14. Then based on the idea of predictive motion vector, using of spatial correlation of adjacent block and global minimum points probability distribution characteristic, predictive diamond searching ( pds ) and its advanced mode : adaptive pds ( apds ) are introduced. finally the algorithm of pds and apds and its simulation results comparing with conventional me algorithm are given

    然後基於預測性運動矢量的概念，利用相鄰塊運動矢量的相關性和全局極值點概率分佈特性，提出了預測性菱形搜索演算法和它的改進演算法：自適應預測性菱形搜索法，設計出具體演算法，並給出了與傳統快速塊匹配法比較的計算機模擬結果。
  15. The last one is an optimum method using genetic algorithms, which has the advantages of simplicity, strong robust, quick search speed and strong adaptability

    第三種為遺傳演算法優化方法，此方法具有簡單、魯棒性強、搜索速度快和適應性強等優點。
  16. Genetic algorithm ( ga ) is a sort of efficient, paralled, full search method with its inherent virtues of robustness, parallel and self - adaptive characters. it is suitable for searching the optimization result in the large search space. now it has been applied widely and perfectly in many study fields and engineering areas

    遺傳演算法作為一種求解問題的高效并行的全局搜索方法，以其固有的魯棒性、并行性和自適應性，使之非常適于大規模搜索空間的尋優，已廣泛應用許多學科及工程領域。
  17. At last the thesis set up a general ga for nonlinear equations. 6. according to detailed analysis of nonlinear equation, the thesis creates a adaptive variable search scope ga for nonlinear equation

    創造性地提出求解非線性方程的自適應變搜索域遺傳演算法，該方法可同時求解一般的非線性方程與雙函數構成的非線性方程，有效克服了插值解法的不足。
  18. Besides, it is not fit with the precise adjustment and is difficult to conform the place. a new adaptive genetic algorithm with bp algorithm to optimize weight is backed up. the algorithm which combines the merits of the global convergence of genetic algorithm with fast local researching of bp algorithm not only intensifies the gradual convergence and evolution ability but also advance the speed of convergence, precision of training and generalization

    針對傳統遺傳演算法的搜索過程帶有一定的盲目性，其收斂特性不穩定且收斂速度緩慢，特別是在系統規模較大時，優化效果的明顯改善往往需要相當長的時間，而且不適合候選解的精調，難以確定解的確切位置，提出一種新型自適應性遺傳演算法，並在此基礎上，用bp演算法優化前向神經網路權值，綜合了兩種演算法的優點，即遺傳演算法的全局收斂性和bp演算法局部搜索的快速性，強化了遺傳演算法的漸進收斂和進化能力，全面改善了演算法的收斂性，提高了收斂速度及訓練精度，也擴展了泛化能力。
  19. This fact implies that the fractal algorithm is very effective and in practical. 2 ) by combining the tabu search and the clustering technique, we propose a hybird algorithm to solve the placement problems, both for the bbl and the gate - array placement. simulation results show that our hybird algorithm is of robustness and effectiveness, it is expected the algorithm is also uesful in other optimization problems. to testify the feasibility of using various computational intelligent algorithm, such as neural networks, genetic algorithm and ant colony system approach in solving a

    2 ）首次將禁忌搜索演算法與結群技術相結合，並將其分別應用於門陣列布局和bbl布局中，計算機模擬結果表明該演算法魯棒性強、有效，適應性廣，適用於大規模門陣列布局和bbl布局問題， 3 ）分別用神經網路技術、遺傳演算法和蟻群演算法對兩端線網布線問題進行了研究，並對結果進行了分析比較。
  20. In this paper, a fast multi - resolution adaptive motion estimation algorithm is proposed here which using multiple motion vector ( mv ) candidates according to the spatial - temporal correlation in mv fields

    許多演算法沒有考慮各個塊的不同運動特性，搜索范圍是固定的，搜索沒有自適應性，所以，搜索效率並不是很高。
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