搜索能力 的英文怎麼說

中文拼音 [sōusuǒnénglì]
搜索能力 英文
search capability
  • 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; ...
  • 能 : 能名詞（姓氏） a surname
  • 力 : Ⅰ名1 （力量; 能力） power; strength; ability; capacity 2 [物理學] （改變物體運動狀態的作用） forc...
  • 搜索 : 1 （仔細尋找） search for; ferret about; hunt for; scout around 2 [電子學] hunting; scan; [控] in...
  • 能力 : ability; capacity; capability
  1. Udaloy reflects design changes that addressed the shortcomings of the previous krivak program ; namely the lack of helicopter facilities, limited sonar capabilities, and light air - defenses

    勇敢級一改以往克里瓦克級反潛護衛艦的缺點。克里瓦克級不能搭載直升機，搜索能力較低，防空能力也很差。
  2. The experiment results of multiuser detection problem show that both of the proposed methods not only have simpler algorithm structure, but also perform better than conventional qea and bpso in terms of ability of global optimum

    通過對多用戶檢測問題的求解表明，新的演算法不僅操作更簡單，而且全局搜索能力有了顯著的提高。
  3. 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。
  4. The approach not only improves global searching ability of genetic algorithm, but also enhances searching speed

    這種改進方法不僅提高了遺傳演算法全局搜索能力，而且很好的提高了搜索速度。
  5. The objective of the optimal model is to keep the flood process mode similar and subject to restrictions of the actual peak flow discharge and flood volume in different period of time, the ga and prsaa that have global optimal capabilities are used to solve the model in this paper

    在滿足洪峰流量約束和分時段洪量約束條件下，本文建立了以洪水過程模式盡量相似為目標的洪水過程放大優化模型，並採用具有全局搜索能力的遺傳演算法和并行組合模擬退火演算法求解該模型。
  6. Then, an improved genetic algorithm is proposed to solve this problem. this algorithm makes trees with the source and all destinations are the space of operation and filter operation. with hybrid selection operator, competition among brothers, greedy operation, filter operation

    然後給出了一種基於遺傳演算法的實時多播路由選擇方法，並用改進的遺傳演算法進行了求解，該演算法採用包含源節點和目的節點的樹作為交叉和變異的空間的方法，通過加入混合選擇、小范圍競爭擇優的交叉變異操作，提高了全局搜索能力和收斂速度。
  7. Because ga possesses the traits of can global random search, the robustness is strong, been use briefly and broadly, it didn ’ t use path search, and use probability search, didn ’ t care inherence rule of problem itself, can search the global optimum points effectively and rapidly in great vector space of complicated, many peak values, cannot differentiable. so it can offset the shortages of nn study algorithm, can reduce the possibility that the minimum value get into local greatly, the speed of convergence can improve, interpolation time shorten greatly, the quantity of training reduce

    因為遺傳演算法具有全局隨機搜索能力，魯棒性強、使用簡單和廣泛的特點，它不採用路徑搜索，而採用概率搜索，不用關心問題本身的內在規律，能夠在復雜的、多峰值的、不可微的大矢量空間中迅速有效地尋找到全局最優解，所以可以彌補神經網路學習演算法的不足，使陷入局部最小值的可能性大大減少，使得收斂速度提高，訓練量減小。
  8. At first, in order to prevent the premature convergence of genetic algorithm effectively, the author brings forward a novel dyadic floating - point supplementary mutation operator. then, simulating the natural evolution, the author presents a novel topology, unoriented - connected topology, for parallel genetic algorithm. in the end, an interval decomposed optimization method is brought forward for ipga, which can improve the optimization performance of the algorithm

    為提高演算法的性能，作者對遺傳演算法進行三種改進：首先，為克服遺傳演算法早熟收斂，作者提出一種新的二元浮點補碼變異運算元；其次，模擬生物自然進化模式，為并行遺傳演算法提出了一個新的并行拓撲結構- - - -無定向拓撲連接；最後，作者提出一種區間分解優化思想，來提高對最優解的搜索能力。
  9. Adaptive mutation probabilities in genetic algorithms with local search ability

    具有局部搜索能力的自適應變異遺傳演算法
  10. The global random searching ability of adaptive evolutionary programming algorithm and high evolutionary ability by the method in this paper is illustrated by the result of actual power systems

    算例表明，論文演算法不僅保留了自適應進化規劃演算法的全局搜索能力，而且還具有高效的進化能力。
  11. The overall effects of two typical web page visual design modes ( rich and plain ) and two language systems ( chinese and english ) on world wide web user visual search performances in 3 variables ( searching time, errors and satisfaction ) were studied

    摘要考察兩種典型網頁視覺設計形式（豐富與簡練）及兩種語言系統（中文與英語）對用戶視覺搜索能力在搜索時間、錯誤及滿意度三個變量上的綜合性影響。
  12. Sofm neural networks is embedded into evolutionary strategy ( es ). fitness function is constructed based on the state of sofm neural networks. the sensitivity of sofm neural networks to initial weight matrix and sequence of input exemplars is overcome by the strong global optimum of es

    將sofm網路嵌入到進化策略（ es ）中，根據sofm網路的運行狀態構造es的適應性函數，利用es的強搜索能力，克服sofm網路聚類效果受輸入模式次序和網路初始連接權矩陣的影響。
  13. Thirdly, the weight and threshold of bp neural network model was optimized by genetic algorithm ( ga ), which has stronger macroscopic search and global optimization property, based on bp network model of the preparation of superfine quartz powder. this model is named ga - bp, and improves the generalization capability and the parameters forecast precision of bp network model, and was proved to be correct by both theoretical analysis and experiment

    再次，本文以粉石英制備的bp網路模型為基礎，利用遺傳演算法（ ga ）較強的宏觀搜索能力和良好的全局優化性能，對bp網路模型的權值和閾值進行優化，極大地提高了bp網路模型的泛化性能和參數預測精度，將經過ga優化后的bp網路模型簡稱為ga - bp網路模型。
  14. Based on the global stochastic searching method of classic genetic algorithm ( ga ), and using the diversity preservation strategy of antibodies in biology immunity mechanism, the method greatly improves the colony diversity of ga and has better global searching capability

    該演算法在傳統遺傳演算法全局隨機搜索的基礎上，借鑒了生物免疫機制中抗體的多樣性保持策略，改善了遺傳演算法的群體多樣性，具有更好的全局搜索能力。
  15. According to an analysis of the current various optimum methods, a new mixed type of genetic algorithm are proposed, which overcomes some typical limitations such as the decrease of hunting efficiency lack of hunting competence near the optimal solution. with a model for optimum design setup, the system brwcad are worked out with the advanced language visual basic6. 0 and the object - oriented technique

    此外，針對衡重式擋土墻常規設計存在的弊病，指出其優化設計的必要性與重要性，並在比較分析已有優化方法優缺點的基礎上，引入並提出了一種新型混合遺傳演算法進行優化設計，解決了臨近最優解搜索效率降低、搜索能力不足等缺陷。
  16. A study on the user visual search performances for web visual design

    針對網頁視覺設計的視覺搜索能力研究
  17. Abstract : in this paper, we propose an improved lagrangian relaxation algorithm to solve job - shop scheduling problems. besides the addition of augmented objective, we expand the search scope of near - optimal solutions and improve the computational efficiency greatly by restricting the solution scope of sub - problems and modifying the search method of dual problem. at the same time, we develop a genetic algorithm combining with the lr ( lagrangian relaxation ) method. using the numerous useful solutions we get in the lagrangian relaxation as the original genes, we can improve the solution further. test results show that these methods achieve satisfied outcome for job - shop problems. they can also be applyed to other programming problems with constraints

    文摘:針對車間調度問題，提出了一種改進的拉氏鬆弛演算法.在增加輔助目標函數的基礎上，通過對子問題的限制和搜索策略的改變，使拉氏演算法的計算量減少，近優解的搜索能力有很大改善.本文還提出了一種基因優化演算法，充分利用拉氏演算法得到的多個近優解，進一步優化結果.模擬結果表明對車間調度問題得到了較好的結果.本方法也可用於其它有約束的規劃問題
  18. The proposed genetic - tabu algorithms, which are based on the parallel search main flame provided by genetic algorithms, integrating biology evolution of genetic algorithms and local search of tabu search which can avoid circuit search, can solve global optimization problems quickly

    本文提出的遺傳禁忌搜索演算法基於遺傳演算法提供的并行搜索主框架，結合遺傳群體進化和禁忌搜索演算法較強的具有避免迂迴搜索能力的鄰域搜索，可以實現快速全局優化。
  19. This hybrid algorithm take advange of local search of pattern search and whole search of genetic algorithm. it first confines the direction of large scale search to the area of high fitness by genetic algorithm, and then utilizes pattern search to search in the small area got by the searching of genetic algorithm., thereby the optim value is got

    該方法利用了單純形法的局域搜索能力和遺傳演算法的全局搜索能力，通過遺傳演算法控制大范圍搜索的方向，使得搜索向著適應度值高的區域發展，再通過單純形法在遺傳演算法搜索到的區域內進行小范圍的鄰域搜索，從而能夠得到高適應度值域的最優值。
  20. * search provides full - text search capability within a web site

    *搜索提供在站點中的全文搜索能力。
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