- 克利金法
- indicator: n. 1.指示者；指示物；標(biāo)識(shí)。 2.【化學(xué)】指示劑。 ...
- kriging: 克里格法; 克里金; 克利金法
- blocking kriging: 分塊克里格方法
- disjunctive kriging: 析取克里格
- kriging estimator: 克里格估計(jì)量
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indicator kriging中文什么意思
- 克利金法
下載手機(jī)詞典可隨時(shí)隨地查詞查翻譯
例句與用法
- Indicator kriging study of multivariate information in temporal - spatial domain
時(shí)空多元指示克立格法的理論研究 - For each point x in the feature space , the proposed algorithm calculates the probabilities that x belongs to each individual classes using indicator kriging , and then assign x to the class with highest probability
研究中我們將各種類別在特徵空間之分布視為一個(gè)指標(biāo)變數(shù)之隨機(jī)變域，并發(fā)展一個(gè)以指標(biāo)變域空間推估為基礎(chǔ)之新的分類理論。 - The analysis and design class diagram are given . the sequence indication stochastic simulation algorithm based on indicator kriging is realized . the algorithm applies to discrete and continuous variable has no restrict to data distribution
系統(tǒng)給出了沉積相隨機(jī)建模的分析類圖和設(shè)計(jì)類圖，實(shí)現(xiàn)了基于指示克里金估計(jì)的序貫指示隨機(jī)模擬算法，該算法對(duì)離散數(shù)據(jù)和連續(xù)數(shù)據(jù)都適用，不要求數(shù)據(jù)的分布特征，可以較好的模擬相特征。 - Synthesizing multivariate information , au - comprehensive chemical exploratory anomaly was discussed with geostatistical methods at guilaizhuang au - deposit . main work included : using cokriging , influence of regional chemical elements w , as , sb to au - anomaly and au - mineralization has been studied . contribution of g au ag to au - anomaly has been probed into making use of indicator kriging and some suggestions for the future work have been given . key words : multivariate information ; au - comprehensive chemical exploratory anomaly ; geostatistics ; cokriging ; indicator kriging
綜合多元信息，對(duì)歸來(lái)莊金礦床綜合化探金異常進(jìn)行地質(zhì)統(tǒng)計(jì)學(xué)研究，主要作了如下工作：利用協(xié)同克立格法研究化探元素w , as , sb對(duì)au異常和au成礦的影響，利用指示克立格法研究g au ag對(duì)形成au異常的貢獻(xiàn)，并對(duì)今后工作提出建議。 - The proposed indicator kriging classification algorithm has the following advantages : ( 1 ) it can deal with anisotropic problem in feature space , ( 2 ) it is a nonparametric method , and need not to know the type of probability distribution , and ( 3 ) it yields 100 % classification accuracy for the training data
此分類法具有如下之優(yōu)點(diǎn)： ( 1 )可處理特征空間中非等向分布之問(wèn)題， ( 2 )該方法屬于無(wú)母數(shù)分類法，不需假設(shè)各類特征之機(jī)率分布類型， ( 3 )對(duì)訓(xùn)練像元之分類正確率可達(dá)100 。