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  • 例句與用法
  • Using the conic function model local approximation , w . cdavidon ( 1980 ) proposed a class of iterative algorithms with modified matrix combining function value , furthermore under the theory d . c . sorensen has used local quadratic approximation method , then applying collinear scaling idea improving on the above algorithm and generalizing it , getting a class of collinear scaling algorithm , unifying former quasi - newton . in the paper , using local quadratic approximation method , the first , constructing the new collinear scaling gene , getting a class of the new collinear scaling algorithm with briefness and numerical stability , . , we discusses some properties of the algorithm and its local linear convergence , q - superlinear convergence and the whole convergence ; secondly we have made numerical experimentation and numerical analysis ; the last , we have done much discussion for collinear scaling idea and given the several new collinear scaling algorithm
    本文的工作就是基于局部二次逼近原理,首先通過構(gòu)造新的共線調(diào)比因子,得到了一類新的更簡(jiǎn)潔,數(shù)值穩(wěn)定性更好的共線調(diào)比算法,進(jìn)而我們給出了本共線調(diào)比算法的局部收斂性,全局收斂性以及算法q -超線性速度的理論證明;其次,用經(jīng)典的無約束優(yōu)化五大考核函數(shù)就本共線調(diào)比算法進(jìn)行了數(shù)值試驗(yàn)和數(shù)值分析;最后,就局部二次逼近思想,進(jìn)行共線調(diào)比算法思想進(jìn)行更廣泛的討論,給出了幾個(gè)新共線調(diào)比算法。
  • The main research objects are transferred structure control stochastic system . according to the condition of the system , a decision maker ( a man or a computer ) should select a way to control or affect the transfer of the system , so that each way decides the aimed function value of the stochastic process and the corresponding ones
    其主要研究對(duì)象是轉(zhuǎn)移結(jié)構(gòu)受控的隨機(jī)系統(tǒng),根據(jù)系統(tǒng)的狀態(tài),決策者(如人類或計(jì)算機(jī))選取一個(gè)策略來控制或影響系統(tǒng)的轉(zhuǎn)移,從而每個(gè)策略可定義一個(gè)隨機(jī)過程和相應(yīng)于該過程的目標(biāo)函數(shù)值, mdp的目的是選取一個(gè)好的控制策略。
  • One method which can obtain best scheduling rule set in specific manufacture environment is proposed , genetic algorithm and process simulation is integrated in this method , process simulation is used to get adaptive function value and genetic algorithm is used to search optimum solution . and , for lessening calculation time , serial genetic algorithm is replaced by parallel genetic algorithm
    提出了一種將遺傳算法和過程仿真相結(jié)合的調(diào)度規(guī)則選擇方式,它以過程仿真求取適應(yīng)度函數(shù)值,應(yīng)用遺傳算法進(jìn)行優(yōu)化,從而完成特定生產(chǎn)環(huán)境下的調(diào)度規(guī)則選擇問題;并以主從式并行遺傳算法代替?zhèn)鹘y(tǒng)遺傳算法,從而保證了最終解在時(shí)間上和質(zhì)量上的可行性。
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