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classical statistics中文是什么意思

  • 經(jīng)典統(tǒng)計法
  • 經(jīng)典統(tǒng)計學(xué)

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  • The theoretical base of this method proposed in the paper are the classical statistics theory and computer simulation method
    本文提出的方法的理論基礎(chǔ)是經(jīng)典的統(tǒng)計學(xué)理論,包括控制論方法與計算機(jī)仿真方法。
  • The usual method is , to find a sub - missile disper firstsion center first from each group data of the sub - missile ' s falling point coordinate , then to estimate the parameters according to a few data of dispersion center using the classical statistic method
    通常的方法由每次試驗的子彈落點數(shù)據(jù)獲得一個子彈散布中心,再由少數(shù)的幾個散布中心數(shù)據(jù)、運用經(jīng)典的統(tǒng)計方法求散布中心的正態(tài)總體分布參數(shù),其不足之處在于小樣本條件下采偽的概率很高。
  • This research investigated the variability and the quantitative relationships among soil nutrients ( soil ph , total n , organic matter , available p ) , growth status ( spad , lai and spad lai ) and yield of rice . all data were analyzed by both classical statistics and geostatistics based on gis . by further integrating gis , gps and crop management knowledge model , a decision support system for precision farming ( dsspf ) was developed , which laid a technical foundation for the practical application of precision farming system
    本研究基于gis技術(shù),以經(jīng)典統(tǒng)計和地統(tǒng)計學(xué)為分析手段,確立了田區(qū)土壤養(yǎng)分(土壤ph 、全氮、有機(jī)質(zhì)、速效磷、速效鉀) 、水稻作物長勢( spad 、 lai 、 spad * lai )和產(chǎn)量的空間變異特征及定量關(guān)系;進(jìn)一步以作物管理知識模型為智能決策支撐,提出了gis與模型及gis與gps的組件化集成技術(shù),構(gòu)建和實現(xiàn)了基于田區(qū)作物產(chǎn)量、土壤養(yǎng)分和苗情監(jiān)測差異的精確農(nóng)作決策支持系統(tǒng)( dsspf ) ,為精確農(nóng)作系統(tǒng)的應(yīng)用奠定了技術(shù)基礎(chǔ)。
  • Currently , image recognition has five primary methods : classical statistic model method , auto method based on information , auto method based on model , amalgamation of several sensors and manual neural network . how to improve the classical method and how to assemble different recognition method are still problems to be improved . based on the current research state , the classical statistic model recognition method and correlative knowledge are researched firstly
    基于當(dāng)前的研究現(xiàn)狀,本文以可見光和紅外儀器同步拍攝的不同環(huán)境下的運動車輛目標(biāo)序列為對象,在深入研究了經(jīng)典的統(tǒng)計模式識別方法及相關(guān)理論的基礎(chǔ)上,對車輛目標(biāo)識別系統(tǒng)中的特征提取和識別方法等方面做了較深入的研究,并對神經(jīng)網(wǎng)絡(luò)在車型識別系統(tǒng)中的應(yīng)用作了試探性研究。
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