random searching造句
例句與造句
- I guess she meant what she said . they ' re just doing a random search
我猜她說話算話，他們只是在做一項抽查而已。 - Traditional optimization techniques search for the best solutions using gradients or random searching
傳統(tǒng)的最優(yōu)化技術(shù)大多是基于梯度尋優(yōu)技術(shù)或隨機搜索的方法。 - Adaptive mutation algorithm has been adopted to ensure the global random searching speciality for feasible individual
而對可行個體,則采用自適應(yīng)變異算法,以保證算法的全局性隨機搜索特性。 - Then the article chooses the mechanical system , builds up the smelling robotic system , and programs the software of the system based on the half - random searching algorithm
最后選用機械本體和硬件系統(tǒng)組合,構(gòu)建了嗅覺機器人系統(tǒng),并根據(jù)半隨機搜尋策略編制了軟件。 - To overcome this difficulty , a newly proposed random search algorithm particle swarm optimization was applied to a global optimization method for the wastewater treatment network design
因此，提出了應(yīng)用新型隨機型算法粒子群優(yōu)化算法求解上述復(fù)雜非線性最優(yōu)化問題。 - It's difficult to find random searching in a sentence. 用random searching造句挺難的
- 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,論文算法不僅保留了自適應(yīng)進化規(guī)劃算法的全局搜索能力,而且還具有高效的進化能力。 - Because the search procedure will be adjusted according to the previous result , the method not only speeds up the random search but also balances the global and local demands ( adaptive equalization )
因為在搜索過程中會根據(jù)搜索中間結(jié)果進行調(diào)整，所以此方法不僅可以加快搜索速度，而且可以平衡全局和局部搜索需求。 - Compared with the computational result of traditional ga , it shows that the searching efficiency of ga can be improved remarkably and the fluctuation of random searching can be reduced by recognizing building block
與基本遺傳算法的計算結(jié)果對比分析表明，所提算法可顯著提高遺傳算法的搜索效率，減小遺傳算法隨機搜索的波動性。 - A genetic algorithm ( ga ) based on building block recognition was proposed , in which building block candidates were recognized in evolving process to speed up the search so as to avoid the blindness of ga random searching
摘要提出了一種基于積木塊識別的遺傳算法，該算法通過對進化過程中的候選積木塊進行識別與利用來加速搜索，從而避免遺傳算法隨機搜索的盲目性。 - It seemed to be a genuine meeting of minds , old and new the analogue organisers of the world ' s information handing it on to a digital successor responsible for organising 8 billion web pages according to random search requests
這似乎是新老觀念的一次真正匯合：模擬格式世界信息的管理者，將這些信息傳遞給他們的數(shù)字繼任，由其按照任意搜索請求對80億張網(wǎng)頁進行整理。 - By comparing these two methods , we show the advantages of quasi - monte carlo method . we also introduce the standard monte carlo random search for optimization . the last but not least application is metropolis algorithms which is the origin of monte carlo method
第1章介紹了蒙特卡羅和擬蒙特卡羅積分的誤差估計并闡述了擬蒙特卡羅方法的優(yōu)勢，同時介紹了擬蒙特卡羅的標準優(yōu)化方法，最后介紹了蒙特卡羅方法的起源? metropolis模擬方法。 - We also do a further research on constructing comprehensible classification rules using niche - based ga and finding interesting classification rules using adaptive ga . genetic algorithm is an overall random searching method based on the theory of evolution and molecular genetics
本文對遺傳算法進行分類規(guī)則挖掘進行了研究，并在此基礎(chǔ)上，進一步研究了基于小生境遺傳算法挖掘易于理解的分類規(guī)則和基于自適應(yīng)遺傳算法發(fā)現(xiàn)有趣分類規(guī)則的技術(shù)。 - 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,它不采用路徑搜索,而采用概率搜索,不用關(guān)心問題本身的內(nèi)在規(guī)律,能夠在復(fù)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(yōu)解,所以可以彌補神經(jīng)網(wǎng)絡(luò)學(xué)習(xí)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(xùn)練量減小。 - Aimed at multiple - limit , multiple - object , non - linear , discrete of voltage / var optimization and control , on account of whole evolution of evolutionary programming , no demand for differentiability of optimal function , and random search , it can obtain global optimum with mayor probability , this paper solve optimal function with evolutionary programming
在對優(yōu)化的具體實現(xiàn)過程中，由于進化規(guī)劃著眼于整個整體的進化，對于所求解的優(yōu)化問題無可微性要求，采用隨機搜索技術(shù)，能以較大的概率求解全局最優(yōu)解的特點，針對電壓無功控制模型是一個多限制、多目標、非線性、離散的優(yōu)化控制問題，因此應(yīng)用進化規(guī)劃算法進行模型的求解。
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