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- A recursive prediction error algorithm which converges fast is applied to tra. 采用了收斂速度較快的遞推預報誤差算法訓練神經(jīng)網(wǎng)絡(luò )。
- The paper introduces the grey forecasting model and analy ses its prediction error as well as application in detail. 詳細介紹了灰色預測方法并分析了預測誤差及其實(shí)用價(jià)值。
- An MD prediction error coding method is also proposed using low quality macroblock update. 該方案在丟包環(huán)境下取得較好的抗丟包性能。
- It is proved to have the same asymptotic statistical properties as the prediction error method(PEM). 證明了該方法與預報誤差法具有相同的漸近和統計性能。
- The prediction formula and its error estimation are also established.Its regression and time-varying autoregression model is presented. 在此基礎上建立時(shí)變序列預測公式及誤差估計公式，給出其回歸與時(shí)變自回歸模型。
- My research concentrates on discretization of model optimal control problem, development of the posteriori error estimator and designment of efficient solver for discrete optimal control problem. 我的研究在于為模型最優(yōu)控制問(wèn)題提供離散方案，進(jìn)行誤差估計以及設計快速求解算法。
- In the method, the criterion of final prediction error (FPE) is employed to determine the embedding dimension of samples. 該方法應用最終預報誤差(FinalPrediction Error,FPE)準則確定樣本的嵌入維數。
- Based on the method of minimum prediction error control, a multiple model adaptive controller( MMAC) for discrete time is presented. 基于最小預測誤差控制器設計方法,設計離散時(shí)間系統多模型自適應控制器,并引入“局部化”方法。
- Example for error estimation of phasor induction log is given. 根據置信區間的指標,文章給出了相量感應測井誤差估計的實(shí)例。
- Through comparing their sums of squared error,it was concluded that prediction error algorithm-based OE model has the best precision. 通過(guò)誤差平方和的比較,確定利用基于輸出誤差(OE)模型的預報誤差法所建立的模型的精度最高。
- Based on the difference between the corresponding limit of displacement from both side of contacted bodies, a local direct error estimator of BEM solution for 3D elastic contact problem is presented, and then a scheme of adaptive BEM is suggested. 在此基礎上提出將接觸體接觸單元間與域內解連續的邊界位移之差的某種度量作為三維彈性體接觸問(wèn)題邊界元法的一種誤差直接估計，并且提出了三維彈性體接觸問(wèn)題邊界元法的一種自適應計算方案。
- Based on the method of minimum prediction error control, a multiple model adaptive controller (MMAC) for discrete time is presented. 基于最小預測誤差控制器設計方法,設計離散時(shí)間系統多模型自適應控制器,并引入“局部化”方法。
- Then the NN model is trained and the average prediction error is 26.46%, which reaches the demand of environmental management. 經(jīng)過(guò)網(wǎng)絡(luò )訓練，預測平均誤差為26.;46%25，滿(mǎn)足環(huán)境管理的精度要求。
- The algorithm prediction error is larger under ionospheric stormy conditions, which is more prominent for the stations in the low latitudes. 此次磁暴期間，算法的精度明顯降低，對于低緯地區的影響更為顯著(zhù)；
- RPE (recursive prediction error) algorithm with the advantage of fast convergence is applied to training the recurrent neural network. 采用遞推預報誤差算法訓練神經(jīng)網(wǎng)絡(luò )，具有收斂速度快、收斂精度高的特點(diǎn)。
- This error estimation model can be applied in all different processes of RP. 該公式適用于RP技術(shù)的各種工藝方法，具有普遍意義；
- Probabilistic principal component analysis (PPCA) can realize the process monitoring according to the whiten values of process variables prediction error and their scores. 摘要概率主元分析(PPCA)能夠根據過(guò)程變量的預測誤差及其主元的白化值實(shí)現對過(guò)程的監控。
- We prove a priori error estimate of this new method.We also give residual-type a posteriori error estimator of it.Numerical experiments are carried out to support our theory. 對此法進(jìn)行了先驗誤差分析并給出其殘量型后驗誤差估計，且通過(guò)數值實(shí)驗驗證了該方法及其自適應方法的有效性。
- The results show that the algorithm quickly stabilizes, has a very small prediction error, and quickly responds to RTT changes, so it can improve transmission performance. 試驗結果證明，所提出的算法相比于原算法，具有能很快達到穩定，穩定后的預測誤差小，對RTT變化的響應快等特點(diǎn)，提高了傳輸性能。
- A case study in Xilin Gole league shows that this method could get a better result with the least prediction error and more abundant spatial information. 以錫林郭勒盟為例進(jìn)行分析的結果表明，本方法得到的整體及局部的誤差估計均小于傳統插值方法，并且在空間信息上表現出更為豐富的空間變異信息。
