MrBush asked in 社會與文化語言 · 1 decade ago

可以幫忙翻譯以下幾段英文嗎?急用(10點)

A new method for optimization of continuous nonlinear

functions was recently introduced [6]. This paper reviews

the particle swarm optimization concept. Discussed next

are two paradigms that implement the concept, one

globally oriented (GBEST), and one locally oriented

(1,131 IST), followed by results obtained from applications

and tests upon which the paradigms have been shown to

perform successfully.

Particle swarm optimization has roots in two main

component methodologies. Perhaps more obvious are its

ties to artificial life (A-life) in general, and to bird

flocking, fish schooling, and swarming theory in

particular. It is also related, however, to evolutionary

Computation, and has ties to both genetic algorithms and

evolution strategies [ 11.

I’armlc swarm optimization comprises a very simple

concept, and paradigms are implemented in a few lines of

computer code. It requires only primitive mathematical

operators, and is computationally inexpensive in terms of

both memory requirements and speed. Early testing has

found the implementation to be effective with several

kinds of problems [6]. This paper discusses application of

the algorithm to the training of artificial neural networkweights. Particle swarm optimization has also been

demonstrated to perform well on genetic algorithm test

functions, and it appears to be a promising approach for

robot task learning.

3 Answers

Rating
  • 怡樺
    Lv 6
    1 decade ago
    Favorite Answer

    新的方法為了最優化的連續的非線性的功能最近被介紹[ 6 ]. 這紙回顧粒子蜂群最優化思想. Discussed下一個2個範例是執行思想, 一globally朝東( GBEST),和1局部地朝東( 1131 IST),跟隨附近結果獲得從應用和測試在上哪個範例使被顯示了順利地履行.粒子蜂群最優化有深植於2主要的成分方法論. 或許更明顯的是它的結到人造生命(一-生命)一般說來,和鑑別鳥類聚集,魚學費,和液晶攢動說在特殊的. 它也被敘述, 然而,進化的計數,和有結到雙方的遺傳學的運演算法則和發展戰略 [ 11.我'armlc蜂群最優化包含非常簡單的思想,和範例被執行在一些線路的電腦代碼. 它僅僅需要原始的精確的操作者,和computationally廉價的根據雙方的記憶體需求和速度. 早測試有發現履行是有效的和個別的有幾分問題[ 6 ]. 這紙討論應用的運演算法則到訓練的人造的神經系統的networkweights. 粒子蜂群最優化也是示範履行好上遺傳學的運演算法則試驗功能,和它出現是有希望的接近為了機器人任務學習.

    Source(s): 網路...
  • 1 decade ago

    .... 怎麼還是看不懂

  • A new method for optimization of continuous nonlinear

    functions was recently introduced [6]. This paper reviews

    the particle swarm optimization concept. Discussed next

    are two paradigms that implement the concept, one

    globally oriented (GBEST), and one locally oriented

    (1,131 IST), followed by results obtained from applications

    and tests upon which the paradigms have been shown to

    perform successfully.

    Particle swarm optimization has roots in two main

    component methodologies. Perhaps more obvious are its

    ties to artificial life (A-life) in general, and to bird

    flocking, fish schooling, and swarming theory in

    particular. It is also related, however, to evolutionary

    Computation, and has ties to both genetic algorithms and

    evolution strategies [ 11.

    I’armlc swarm optimization comprises a very simple

    concept, and paradigms are implemented in a few lines of

    computer code. It requires only primitive mathematical

    operators, and is computationally inexpensive in terms of

    both memory requirements and speed. Early testing has

    found the implementation to be effective with several

    kinds of problems [6]. This paper discusses application of

    the algorithm to the training of artificial neural networkweights. Particle swarm optimization has also been

    demonstrated to perform well on genetic algorithm test

    functions, and it appears to be a promising approach for

    robot task learning.

    中文

    為連續的非線性作用的優化最近介紹了一個新的方法[6]。 本文回顧微粒群優化概念。 其次被談論實施概念的二個範例, 全球性地針對的一(GBEST), 并且當地針對的一(1,131 IST), 由從範例顯示成功地表現的應用和測試得到的結果跟隨。

    微粒群優化有根在二主要成份方法學。 或許更加顯然的一般來說,是它的領帶到人工生命(生活) 并且到鳥聚集, 魚教育, 并且成群移動理論特別是。 它也被關係, 然而, 到演變計算,并且有依靠基因算法和演變戰略[11。

    I』 armlc群優化包括一個非常簡單的概念, 并且範例在計算機編碼幾條線被實施。 它要求只有原始數學操作員, 并且計算上是低廉的根據內存要求和速度。 及早測試發現實施是有效的與數種類[第6個問題]。 本文談論算法的應用到人為神經系統的networkweights訓練。 微粒群優化也是展示很好執行在基因算法測試功能, 并且看起來是一項可行措施為機器人任務學會。

    Source(s): -------------
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