算法分類的英文

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英文翻譯
造句

algorithm classification

算法 algorithm
分類 classify
地址計(jì)算法分類 address calculation
算法分解 algorithm decomposition
算法分析 algorithm analysis; analysis of algorithm
我想“算法分析 analysis of algorithms
二分法分類 binary sort; classification by dichotomy
方法分類圖 method taxonomy diagram
兩分法分類 dichotomous classification
濕法分類 classification with water
文法分類 grammar category
無法分類型 unclassified
語法分類 syntactic category; syntactic class
數(shù)列算法分析 fib's algorithms analyses
中圖法分類號 clc
計(jì)算機(jī)算法分析 analysis of computer algorithm
算法分析與設(shè)計(jì) analysis and design of algorithms
分類算法 sorting algorithm
地面采礦法分類 surface mining methods
梭織品織法分類 type of weave
報(bào)文分類算法 message digest algorithm (md5)
幻序分類算法 magic order sorting algorithm
數(shù)據(jù)分類算法 data-sorting algorithm
順序分類算法 sequential classification algorithm
陣列分類算法 array sorting algorithm; arraysorting algorithmm

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We evaluate error rate , scalability , time , tree nodes numbers by 12 - cross validation method . experiment has demonstrated that new algorithm greatly reduces the error rate and has good scalability at the same time
實(shí)驗(yàn)中采用12交又驗(yàn)證方法，對算法分類準(zhǔn)確率、伸縮性、時間、樹節(jié)點(diǎn)個數(shù)等幾個指標(biāo)進(jìn)行評估。
A learning algorithm of compressed candidates based on bayesia belief network is developed to solve slow running problem of traditional bayesian belief network constructing algorithm
摘要針對傳統(tǒng)算法分類速度較慢的不足，改進(jìn)傳統(tǒng)算法中候選變量的搜索方式，提出用依賴度量函數(shù)測量變量之間的依賴程度，得出壓縮候選的貝葉斯信念網(wǎng)絡(luò)構(gòu)造算法。
Then we describe the lastest researches and developments on multicast congestion control algorithms and classify them from different aspects . furthermore , different algorithms are analyzed and compared , and some problems are pointed out
然后討論了組播擁塞控制算法分類的標(biāo)準(zhǔn)，比較和分析了現(xiàn)有組播擁塞控制算法的優(yōu)缺點(diǎn)，指出了其中的不足之處。
There are two different visualization approaches of 3d - data sets , one is surface rendering algorithm , the other is volume rendering algorithm . the latter is the emphasis of the paper . the paper describes its optical modek algorithm classification and discusses its future applications and problems to be solved
體繪制算法是本文的研究重點(diǎn)，本文介紹了體繪制算法的光照模型、算法分類和發(fā)展方向，并以光線投射算法為例，詳細(xì)的論述了體繪制算法的原理、流程、關(guān)鍵技術(shù)。
In algorithms , classification algorithms are divided into two cases : one for known statistical distribution model and the other for unknown statistical distribution model . four classification algorithms , the bata - prime statistic model fusing quadratic gamma classifier , based on sar image rcs reconstruction and space position mode , on the mixed double hint layers rbfn ( mdhrbfn ) model and on the self - adapt fuzzy rbfn ( afrbfn ) model , are derived . the problems , including how to further improving the class ratio of the bayes decision , decreasing the dependence on the statistical model and directly providing the adapted algorithm with samples , are solved
提出了基于徑向基函數(shù)神經(jīng)網(wǎng)絡(luò)( rbfn )的雙隱層混合網(wǎng)絡(luò)( mdhrbfn )模型，解決了標(biāo)準(zhǔn)神經(jīng)網(wǎng)絡(luò)在具體sar圖像地物分類中分類類別數(shù)目不夠和分類精度差的問題；提出了基于模糊推理系統(tǒng)的自適應(yīng)模糊rbfn分類( afrbfn )模型，兼顧通用性與精確性，增強(qiáng)人機(jī)交互能力，進(jìn)一步提高了算法分類率。
It can make for existing algorithms to be improved by analysing their advantages and disadvantages , and for users to choose a right algorithm for a specified dataset in order to receive a optimization clustering results . it is also the basis of further classifying popular algorithm and establishment of clustering benchmark . secondly , genetic algorithm ( ga ) - based clustering method is researched
分析了現(xiàn)有算法的優(yōu)缺點(diǎn)，以利于進(jìn)一步改進(jìn)；通過對現(xiàn)有算法的性能評述，有利于數(shù)據(jù)挖掘用戶能夠針對特定的數(shù)據(jù)集選擇正確的算法，以獲得最優(yōu)化的結(jié)果和性能；也可以為現(xiàn)有算法分類比較的進(jìn)一步研究以及建立聚類基準(zhǔn)奠定基礎(chǔ)。