樣本回歸函數 的英文怎麼說

中文拼音 [yàngběnhuíguīhánshǔ]
樣本回歸函數 英文
sample regression function
  • 樣 : Ⅰ名詞1. （形狀） appearance; shape 2. （樣品） sample; model; pattern Ⅱ量詞（表示事物的種類） kind; type
  • 本 : i 名詞1 （草木的莖或根）stem or root of plants 2 （事物的根源）foundation; origin; basis 3 （本錢...
  • 回 : 回構詞成分。
  • 歸 : Ⅰ動詞1 （返回） return; go back to 2 （還給; 歸還） return sth to; give back to 3 （趨向或集中於...
  • 函 : 名詞1. [書面語] （匣; 封套） case; envelope 2. （信件） letter 3. （姓氏） a surname
  • 數 : 數副詞（屢次） frequently; repeatedly
  • 樣本 : sample book; specimen; advanced copy; sample; muster; scantling; instance; statistics
  • 函數 : [數學] function函數計算機 function computer; 函數計算器 function calculator; 函數運算 functional operation
  1. On the other hand, they play an important role in the theories of esfimation for regression function. in this paper, we mainly get the large sample properties for partitioning estiona - tion and modified its estimation. for example, we proved their asymptolic normaity under nuture conditions by means of mortingle theory ; we also get their strong consistency for regression function under censored samples ; and finaly we genearzed the result to dependence sample and have strong consistency for the modified partitioning estimation of regression function

    因此本論文研究了回歸函數基於分割估計及改良基於分割估計的大樣本性質，利用鞅的有關理論，在比較自然的條件下，證明了其漸近正態性；首次構造了截尾樣本的回歸函數基於分割估計及改良基於分割估計，並證明其強相合性；同時把有關結果推廣到相依樣本下（如混合） ，獲得了改良基於分割估計的強相合性及收斂速度。
  2. In rsdm, binary patterns are replaced by real - valued patterns, accordingly avoiding the coding process ; the outer learning rule is replaced by regression rule, therefore the model has not only the ability of pattern recognition but the ability of function approximation. the prearrangement of the address array bases on the distribution of patterns. if the distribution of patterns is uniform. then the address array is prearranged randomly, otherwise predisposed with the theory of genetic algorithm and the pruneing measure so as to indicate the distribution of patterns and improve the network performance. non - linear function approximation, time - series prediction and handwritten numeral recognition show that the modified model is effective and feasible

    在rsdm中，以實值模式代替二值模式，避免了實值到二值的編碼過程：以回歸學習規則代替外積法，使該模型在具有識別能力的同時具有了對函數的逼近能力；地址矩陣的預置根據樣本的分佈採取不同方法，若樣本均勻分佈，則隨機預置，否則利用遺傳演算法的原理和消減措施來預置地址矩陣，使之反映樣本的分佈，改善網路的性能。
  3. In view of the fact that the genetic algorithm of stochastic programming based on random simulated technology has succeed greatly, this paper points out that changing parameters of genetic algorithm can obtain a sequence of optimum values of goal function. taking these genetic algorithm values as sampling data, we can get fitting optimum function by using multivariate spline regression and get the lipschitzs constant of the fitting optimum function. so for any chance constrained programming problem, we can get its interval estimate

    鑒于基於隨機模擬技術的遺傳演算法在求解隨機規劃問題上的優越性，本文指出，改變遺傳演算法的參數條件，在此基礎上求得機會約束規劃的若干個最優值，以這些最優值為樣本點，利用多元樣條回歸，擬合得到最優值函數，進而求出最優值函數的lipschitzs常數，從而對于任一機會約束規劃問題，都可以得到它的一個區間估計。
  4. In this paper, subjects mainly focused are as follows : to meet with the requirement of forward business and the establishment of mid - long term generation planning of hydroelectric plant, the yearly runoff and the monthly runoff are studied in this paper, providing many kinds models that suited to min - long term runoff forecast, including the time series analysis, the nearest neighbor bootstrap regressive model, the grey topological model, recession curve model, threshold auto regression, mean generating function, and ann model etc. the forecast result proves that these models are useful

    本文從以下幾方面進行了較為深入的研究： （ 1 ）為了滿足水電廠的期貨交易及編制水電站中長期發電計劃的需要，本文對年、月徑流預測進行了研究，提出了徑流中長期預測模型，包括：時間序列模型、最近鄰抽樣回歸模型、灰色拓撲預測、退水曲線模型、門限自回歸模型、均生函數模型及神經網路模型等，從預測成果來看，效果較好。
  5. Regression software programs graph the sample points and give the ( cost - function ) formula of the straight line that best fits the points

    回歸軟體程序將樣本點用圖表示，並且給出最擬合樣本點的直線的價值函數公式。
  6. When solving the problems, we use the support vector regression ( svr ). first assuming the formula of function, then according to the differential and boundary conditions we transform the original problem to the quadratic programming problem. finally, use the learning algorithm of svr to decide the parameters

    只要事先假設出所求函數的表達式，然後根據已知的微分關系和邊界條件對待求函數進行約束將原問題轉化為二次規劃問題，再採用支持向量機回歸演算法對樣本進行學習即可求出參數，確定待定函數的關系式。
  7. Simulation results obtained using both artificial and real data show that the estimation performance of the proposed method is a good approximation of the unknown function and the computation complexity is significantly reduced

    最後對人工和實際的樣本進行了試驗，結果說明了線性規劃支持向量回歸能較好地逼近被估計函數，且計算復雜度明顯降低。
  8. In case of high input dimension system model, taking norm of input vector as the input of wavelet network instead of using tensor product method to construct wavelet network, which could solve the problems of high computation and curse of dimensionality. in the selecting of specific wavelet basis, this thesis first gets initial wavelet basis collection according to spectrum analysis, then gives the least squares regression algorithm to optimize wavelet basis collection based on the least estimation error criteria, which could also initialize the model parameters and increase the speed of convergence

    對于具體的模型小波基函數選擇，本文首先對樣本數據進行時頻域分析，根據小波基函數時頻空間覆蓋樣本時頻空間的原則，在小波框架中選擇建模所用的函數集，然後根據估計誤差最小準則，給出最小二乘回歸優選演算法以進一步優化小波基函數集。
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