random searching 中文意思是什麼
random searching
解釋
隨機查找-
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。 -
Police were everywhere, searching the house almost at random.
到處是警察，搜查房間的行動幾乎毫無章法。 -
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。 -
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。 -
Genetic algorithm is a random searching method which simulates natural selection and evolution. this method has some advantages that other usual methods do n ' t have because of its two characters - - - - - - implicit parallelism and global searching
遺傳演算法是模仿自然選擇與進化的隨機搜索方法，由於其隱含并行性和全局搜索特性，使其具有其他常規優化演算法無法擁有的優點。 -
Recently years, there is a new optimization method named genetic algorithms ( ga ) which is based on the numbers of genus groups. this method is a kind of random searching method which simulated natural selection and evolution. compared with traditional optimization method, genetic algorithms has two notable characters. one character is latent parallel and the other is seaching in the whole area. and genetic algorithms has some advantage which traditional method do n ' t have, for example, in genetic algorithms we did n ' t need the calculation of grade
遺傳演算法[ geneticalgorithms ，簡稱ga ]是近些年來出現的一種模仿自然選擇與進化的基於種群數目的隨機搜索演算法，是優化領域的一個新成員。與常規優化演算法相比，遺傳演算法具有隱含并行性和全局搜索特性這兩大顯著特徵，並具有一些常規優化演算法所無法擁有的優點，如不需梯度運算等。 -
The reason why we integrate them is that k - means algorithm is a mountain climbing method, which is easy convergent to local extremum, and sensitive to the original condition, but its convergent speed is relatively fast, and that genetic algorithm is a random searching method, which can find the whole extremum in a rather big probability, and non - sensitive to the original condition, but its convergent speed relatively slow
之所以將：二者結合在一起，是回為k一均值演算法是一種爬山法，容易收斂到岡部極小值，對初始條件較敏感，但收斂速度較快，而遺傳演算法是卞dl隨機搜索演算法，能夠以較大概率找到全局最憂解，且對們始條件個敏感，但收斂速度較慢。 -
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
摘要提出了一種基於積木塊識別的遺傳演算法，該演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，從而避免遺傳演算法隨機搜索的盲目性。 -
This paper reviewed the history of slope stability analysis, compared all the methods used for slope stability analysis, and analyzed the shortcomings of the methods used for searching the failure surface, for reasons of a lot of uncertainties, for example random uncertainty and fuzzy uncertainty, are existed in the slope engineering
由於邊坡工程中存在著大量隨機性、模糊性等不確定因素，傳統的一些分析、評價方法難以滿足日趨復雜的工程分析與設計要求。本文將遺傳演算法用於邊坡工程的穩定性分析與設計中，根據遺傳演算法（ geneticalgorithms ）的概念，討論了遺傳演算法的基本原理和方法。 -
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
最後選用機械本體和硬體系統組合，構建了嗅覺機器人系統，並根據半隨機搜尋策略編制了軟體。 -
Traditional optimization techniques search for the best solutions using gradients or random searching
傳統的最優化技術大多是基於梯度尋優技術或隨機搜索的方法。 -
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
與基本遺傳演算法的計算結果對比分析表明，所提演算法可顯著提高遺傳演算法的搜索效率，減小遺傳演算法隨機搜索的波動性。 -
All kinds of drawback of traditional method require us searching for a workable method to controlling and forecasting the deep foundation pit dewatering. the random theory is educed into the deep foundation pit dewatering research just in stringent need of practical engineering
傳統方法的種種弊端要求尋求一種可行的方法來對深基坑降水進行控制和預測，隨機理論正是在實際工程的迫切需求下引入深基坑降水工程研究中的。
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