greedy algorithms中文是什么意思

發(fā)音:

中文翻譯
造句

第十六章貪婪算法

greedy adj. 1.貪吃的。 2.貪心的，貪婪的 (for; ...
algorithm n. 【數(shù)學(xué)】算法；規(guī)則系統(tǒng)；演段。
greedy adj. 1.貪吃的。 2.貪心的，貪婪的 (for; after; of)。 3.渴望的，熱望的 (of; for)。 be greedy of gain [honours] 貪財(cái)[名]。 be greedy to do sth. 渴望[急欲]做某事。 adv. -ily ,-iness n.
algorithms 算法式
as greedy as a wolf 貪婪如狼
be greedy for money 棺材里伸手-死要錢(qián)
be greedy for sth 忮求
gluttonous; greedy 貪嘴
greedy algorithm 式演算法; 貪婪算法; 貪婪演算法; 貪心法; 貪心算法; 饕餮法
greedy and mean 貪猥
greedy eyes 貪婪的目光
greedy method 貪心法
greedy monkey 貪吃的猴子
greedy neighbours 惡鄰
greedy scale 貪食圓蚧
inordinately greedy 巴蛇吞象
insatiable; greedy 不知足
the greedy coach 貪婪的教練220
the greedy mob 貪婪之眾
adaptability of algorithms 算法的適應(yīng)性
algorithms for optimization 最優(yōu)化算法
algorithms library 算法庫(kù)
analysis of algorithms 我想“算法分析
approximation algorithms 第三十五章近似算法
cache algorithms 快取文件置換機(jī)制

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例句與用法

Two interactive segmentation methods , snake ( active contour ) and live wire , which are very popular , have been introduced for the medical image segmentation . a snake is a spline curve , which is controlled by an energy equation . to minimize the snake ' s total energy , the finite difference and greedy algorithm have been implemented
論文引入了snake和livewire兩種十分流行的醫(yī)學(xué)圖像交互分割方法，詳細(xì)推導(dǎo)snake的能量方程，實(shí)現(xiàn)了最小化能量方程的有限差分和greedy兩種算法，并利用鄰近圖像的相似性，將其成功應(yīng)用于圖像序列的分割； livewire是一種象素級(jí)的輪廓搜索算法，它在方向圖中找到開(kāi)始點(diǎn)和目標(biāo)點(diǎn)之間的最小代價(jià)路徑。
In the case of the maximal observed area model , the complexity of the problem was studied first , and come to the conclusion that this solve problem of this model is a np problem . so , genetic algorithm ( ga ) and greedy algorithm is applied to solve this problem
對(duì)空間覆蓋率優(yōu)先問(wèn)題,分別應(yīng)用遺傳算法及貪婪算法對(duì)其實(shí)現(xiàn)了近似求解,并通過(guò)對(duì)這兩種不同求解算法的特點(diǎn)及復(fù)雜性進(jìn)行分析,明確了這兩種算法的適用條件;隨機(jī)實(shí)驗(yàn)也進(jìn)一步說(shuō)明了兩種算法的優(yōu)缺點(diǎn)所在。
To deal with the question that how we can guarantee the dna sequences which are stored in the personal dna database are anonymous , that no one can find out whom a special dna sequence is collected from , this paper get a new method ? savior , by improve dnala ( dna lattice anonymization ) , which is a method settling this question . savior replaces the multiple alignment in dnala with pairwise alignment between every tow sequences , and replaces the greedy algorithm in dnala with stochastic hill - climbing . for doing this , it can save the time for data pretreatment , and add the precision of classing
針對(duì)個(gè)人dna數(shù)據(jù)的隱私保護(hù)問(wèn)題,即:如何保證無(wú)法將存儲(chǔ)在數(shù)據(jù)庫(kù)中的dna序列信息與其提供者的個(gè)人身份信息(如:姓名,身份證號(hào)碼等)聯(lián)系起來(lái),本文對(duì)一種新近開(kāi)發(fā)的隱私保護(hù)方法? dnala ( dnalatticeanonymization )進(jìn)行了改進(jìn),在數(shù)據(jù)預(yù)處理階段,用兩兩雙序列比對(duì)代替了原算法中的多序列比對(duì),在不降低處理精度的情況下減少了數(shù)據(jù)預(yù)處理所耗費(fèi)的時(shí)間;用隨機(jī)爬山法代替了原算法中的貪心策略,增加了算法后期處理的精度,從而形成了一種新的算法? savior 。
In the design of corpus , we carefully analyze the syllable distribution of corpus th - coss , then classify the prosodic characters of this corpus and present out the distribution of every prosodic character . based on prosodic character vector , we construct an error function which is used to select original corpus for simulation system , and show the distribution of prosodic characters for the original corpus . greedy algorithm and corpus self - adaptive process are expatiated to set theoretical foundation for text material search
在語(yǔ)料庫(kù)分析與設(shè)計(jì)方面,首先統(tǒng)計(jì)th - coss語(yǔ)料庫(kù)中音節(jié)分布情況,給出th - coss語(yǔ)料庫(kù)韻律特征分類(lèi),并對(duì)每一種韻律特征進(jìn)行統(tǒng)計(jì),然后構(gòu)造了一個(gè)基于韻律特征向量的誤差函數(shù),并采用該誤差函數(shù)提取語(yǔ)料組成模擬系統(tǒng)的初始語(yǔ)料庫(kù),分析該庫(kù)的韻律特征分布,最后闡述了greedy算法與語(yǔ)料自適應(yīng)過(guò)程,為文本語(yǔ)料的搜索打下理論基礎(chǔ)。
In the leach - new protocol , the mainly improvement of the leach protocol exhibits as follow : for the sake of balancing the network load , the network choose the clusters based on the residual energy ; we take multi - hop communication between sensors instead of single - hop communication , which results in the reduction of energy consumption of clusters ; the new protocol finds the path to the cluster head with the minimum cost , using an algorithm similar to flooding to propagate the cost information and greedy algorithm to find the lowest cost link ; the algorithm for assigning tdma time slot reduces overall delays of network
在leach - new協(xié)議中,對(duì)leach協(xié)議的改進(jìn)主要體現(xiàn)在以下幾個(gè)方面:根據(jù)節(jié)點(diǎn)剩余能量選擇簇頭,以平衡網(wǎng)絡(luò)負(fù)載;節(jié)點(diǎn)間采用多跳路由,降低簇頭能量消耗;節(jié)點(diǎn)根據(jù)能量消耗的代價(jià)來(lái)選擇至簇頭的路由,通過(guò)擴(kuò)散算法來(lái)廣播代價(jià)消息,采用貪婪算法來(lái)選擇能量消耗最小的路徑;采用tdma時(shí)隙分配算法減少網(wǎng)絡(luò)時(shí)延。最后,利用ns2仿真軟件進(jìn)行驗(yàn)證。
On the base of implementing greedy algorithm , we put hi - ward an idea of using genetic algorithm into query optimization because of the localization of traditional optimization algorithm while processing multi - join query . moreover , we discuss a series of essential query optimization problems . we also present the test results on the pefformance of optimizer and give the analysis of them
由于傳統(tǒng)查詢(xún)優(yōu)化算法在處理多連接查詢(xún)時(shí)在性能或優(yōu)化結(jié)果上得不到好的效果，在實(shí)現(xiàn)greedy優(yōu)化算法的基礎(chǔ)上，本文提出將遺傳算法應(yīng)用于查詢(xún)優(yōu)化中，從而解決多連接查詢(xún)的優(yōu)化問(wèn)題。
The numerical examples have shown that the parallel algorithm presented for contact - impact simulation on a pc cluster exhibits good parallel efficiency and scalability . a new modified greedy algorithm is presented in this paper which can obtain better length to width ratio through considering the information of nodes
提出了一種修正的greedy算法以完成區(qū)域自動(dòng)劃分的任務(wù)，相對(duì)于傳統(tǒng)的greedy算法，新算法使得分割子域具有更好的長(zhǎng)寬比，且適用于不規(guī)則幾何形狀的有限元網(wǎng)格的區(qū)域劃分。
Therefore , the original optimization model is transformed into the problem of cross sectional area optimization . this paper had great research on the development of optimization algorithm by analyzing typical optimal search method , such as greedy algorithm , simulated annealing algorithm , neural network and genetic algorithm ( ga ) . according to the characteristics of truss structure , we choose genetic algorithm as the solution way
本文在研究?jī)?yōu)化算法發(fā)展過(guò)程的基礎(chǔ)上，分析了典型的優(yōu)化搜索方法：確定性算法如貪婪算法，隨機(jī)搜索算法如模擬退火算法，人工智能算法如神經(jīng)網(wǎng)絡(luò)及遺傳算法，根據(jù)桁架結(jié)構(gòu)優(yōu)化的特點(diǎn)，最終選擇以遺傳算法作為桁架結(jié)構(gòu)優(yōu)化設(shè)計(jì)的主要算法。

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