least squares prediction 中文意思是什麼

least squares prediction 解釋
最小二乘方預測
  • least : adj （little 的最高級，比較級為 less 或 lesser）1 最小的，最少的 （opp most）。2 最不重要的，地位...
  • squares : 方鋼
  • prediction : n. 1. 預言，預告。2. 被預言的事物。3. 【氣象學】預測，預報。
  1. Abstract : artificial neural networks has been applied to simultaneous determination of fluorene and acenaphthene by ultraviolet spectrophotometry. after compared the results of the synthetic samples obtained from the method above mentioned with those from partial least squares ultraviolet spectrophotometry, it shows that satisfied prediction can be obtained by them

    文摘:用人工神經網路-紫外吸光光度法不經分離同時測定芴和苊，並與偏最小二乘-紫外吸光光度法比較.對合成樣品進行分析.結果表明，人工神經網路法同偏最小二乘法一樣能獲得滿意的分析結果
  2. To overcome the disadvantages of the linear calibration methods such as mlr and pls, least - squares support vector machine ( ls - svm ) is introduced to nir quantitative calibration in this thesis. for a set of diesel cetane number ( cn ) samples, the ls - svm model obtains the best performance in the cn prediction, compared with the mlr and pls model

    為克服mlr與pls等線性校正方法的局限性，本文將最小二乘支持向量機（ ls - svm ）演算法用於近紅外光譜的定量校正，並以一批柴油十六烷值樣品數據為例對以上方法進行了比較。
  3. This paper narrates the meaning of research in the applied field of prediction for the ultimate bearing capacity of the integrate pile, introduces several typical predication methods for the ultimate bearing capacity of pile, and gives the way for making model. one of them is the partial least - squares regression method which is put forward by me with the help of mathematics knowledge. the method can offer full range analysis for the ultimate bearing capacity of pile

    本論文主要內容敘述了預測法在完整樁極限承載力中應用研究的意義，引入幾種典型的預測法對樁極限承載力進行預測，闡明了模型的建立方法及過程，其中偏最小二乘回歸預測法是本人藉助數理知識提出的一種新的預測法，用此法可以對樁極限承載力進行全過程分析，本論文最後用marc軟體進行模擬模擬預測，進一步實現了預測的實用性。
  4. Monte carlo simulations were conducted to study the new approaches of qtl mapping, the results indicated that general least squares ( gls ) method, which was widely applied in mixed linear model, could unbiasedly estimate all genetic main effects, including additive effects, dominance effects and epistatic effects of additive by additive, additive by dominance, dominance by additive, dominance by dominance. the interaction effects between genetic main effects and environments could also be predicted unbiasedly by linear unbiased prediction ( lup ). the heterosis prediction based on qtl effects was also unbiased

    對新提出的qtl分析方法進行了montecarlo模擬研究，結果表明，廣泛應用於混合線性模型的廣義最小二乘法（ gls ）能夠無偏估計加性效應，顯性效應以及加加、加顯、顯加、顯顯上位性效應等各項遺傳主效應；運用線性無偏預測法（ lup ）能夠無偏預測上述各項遺傳主效應與環境的互作效應；基於qtl效應的雜種優勢預測也是無偏的。
  5. Based on the least squares and biased estimation especially ridge estimation, a new estimation, that is, generalized ridge estimation is put forward through studies on restriction of the parameter. model ' s prediction being considered, comparison of superiority of optimal and classical predictions with respect to the ridge estimation is showed. regression diagnoses especially distance for principal components estimation is discussed

    論文基於最小二乘估計及有偏估計特別是嶺估計，對參數的約束條件做了進一步研究，並提出一種新型估計即廣義嶺型估計；對模型的點預測問題進行深入探索，得出一種基於嶺估計關于經典預測和最優預測的最優性判別條件；也對回歸診斷特別是基於主成分估計的距離進行了深入探討。
  6. Abstract : the generalized shrunken prediction of finite population is introduced, using generalized shrunken least squares estimator of linear regression models. with respect to prediction mean squared error, a necessary and sufficient condition for superiority of a generalized shrunken prediction over the best linear unbiased prediction is obtained. in the case of linear combination of every unit index, a linear restricting prediction is introduced and then a necessary and sufficient condition for superiority of linear restricting prediction over the best linear unbiased prediction is devived

    文摘:利用線性回歸模型的廣義壓縮最小二乘估計，引入了有限總體的廣義壓縮型預測，在預測均方誤差意義下，得到了廣義壓縮型預測優于最佳線性無偏預測的一個充分必要條件；在只能得到每個個體指標的線性組合時，引入了一種線性約束型預測，並得到了線性約束型預測優于最佳線性無偏預測的一個充分必要條件
  7. The paper establishes the model for the urban life - water quantity prediction by means of combining neural network with the partial least squares method

    將偏最小二乘回歸與神經網路耦合，建立了城市生活用水量預測模型。
  8. Graphically - oriented local multivariate calibration modeling procedures called interval partial least - squares ( ipls ) was applied to select the efficient spectral regions that provided the lowest prediction error

    本研究提出一種間隔偏最小二乘法的農產品近紅外光譜譜區選擇方法，並將其應用於建立蘋果糖度近紅外光譜模型。
  9. Data prediction with few observations based on optimized least squares support vector machines

    基於優化最小二乘支持向量機的小樣本預測研究
  10. Aimed at the character of the agriculture system, the least squares support vector machine prediction model is given based on the principle of the statistical learning theory and structural risk minimization

    針對農業生產系統的特徵，在統計學習理論和結構風險最小化原理的基礎上，建立了基於最小二乘支持向量機的時間預測模型。
  11. In the rls - td ( t ) learning algorithm, the eligibility traces mechanism and the recursive least squares methods are combined together so that better convergence properties can be obtained in learning prediction problems. 2

    Rls - td （ ）學習演算法同時結合了遞推最小二乘參數估計方法和適合度軌跡（ eligibilitytraces ）機制，從而能夠獲得比已有演算法更好的收斂性能。
  12. In the research of the algorithms and theory of temporal difference learning, a new class of multi - step learning prediction algorithms based on linear function approximators and recursive least squares methods is proposed, which are called the rls - td ( t ) learning algorithm. the convergence with probability one of the rls - td ( t ) algorithm is proved for ergodic markov chains, and the conditions for convergence are analyzed

    在時域差值學習（ temporaldifferencelearning ）學習演算法和理論方面，首次提出了一種基於線性值函數逼近的多步遞推最小二乘td （ ） （ rls - td （ ） ）學習演算法，並分析和證明了該演算法在求解遍歷markov鏈學習預測問題中的收斂條件和一致收斂性。
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