forecast error 中文意思是什麼
forecast error
解釋
預報誤差-
The forecast accuracy was proved to be satisfactory with an error ratio less than 6 %
檢測了模型的預測精度，結果顯示誤差小於6 % 。 -
Combining absolute error function with relative error function, and setting it as the objective function of bp networks application to the flood forecast
綜合絕對誤差函數和相對誤差函數於一體，提出一種適合於水文研究的bp神經網路綜合目標函數。 -
Based on the historical space forecast data and corresponding actual data provided by a global semiconductor assembly and test company, the uncertainty of space planning was defined. during this analysis process, linear regression, grey prediction, neural network back propagation algorithm and confidence interval were applied, respectively, to define the uncertainty. compared with those methods, the confidence interval of historical space forecast error, calculated by mathematical statistics, was the reasonable method to define the space forecasting uncertainty
本文從半導體工廠長期生產能力計劃的頂層即廠房生產面積的計劃展開，對一跨國半導體封裝測試公司提供的廠房生產面積的長期歷史預測數據以及對應的真實數據進行分析，採用線性回歸，灰預測，神經網路bp演算法，基於數理統計的置信區間的求解等方法分別定義廠房生產面積預測的不確定度，經多種方法的比較得出，基於數理統計方法求解出的生產面積歷史預測誤差置信區間能直觀清楚地標定不確定度。 -
Then on the basis of calculating result from the prefigurative deviation control structure calculation, " rational data forecast processing about error adjust in prefigurative deviation control was made by the prefigurative theory of bp neural network and corresponding program and software matlab6. 1. at last via the data comparison with the practical survey data draw a conclusion : it is feasible for the construction prefigurative deviation control and error adjust used in pc rigid frame bridges to use the calculation model and program brought forward in this paper
同時，在對預應力混凝土剛構橋施工過程線形預拱度控制的結構計算分析的基礎上，利用bp神經網路的預測理論和相應的程序及軟體包matlab6 . 1對預拱度控制中的誤差調整進行了較好的預測處理，通過與實際施工數據及成橋后測量結果作分析比較，得到結論：運用本論文的計算模型和程序對預應力混凝土剛構橋預拱度控制過程進武漢理工大學碩士學位論文行結構分析和誤差調整處理是可行。 -
Firstly, a coarse forecasting model based on only the primary influencing factor ( that is the weight of iron in matte ) is built using linear regression analysis, then, an error compensating model based on other influencing factors is built to improve the result of forecast
首先應用線性回歸技術建立了僅考慮主要影響因素（銅統含鐵量）的粗略預報模型，而後，應用神經網路技術建立了考慮到多個次要影響因素的誤差補償模型，從而改進預報效果。 -
Aiming at the problem on taking no account of relation of forecast factors and instability of regression results caused by selected factors with no orthonormalization which would bring out error to computational results, monadic linear regression analysis and nature orthonormalization function as well as stepwise regression were integrated to establish forecast models of cold in nanjing and upper respiratory tract infection, cerebral hemorrhage as well as cerebral infarction in jinhua
過去在選擇預報因子時沒有考慮預報因子間的相關性，挑選的預報因子由於非正交使回歸計算的結果不穩定，給計算帶來一定的誤差。針對這一問題，文章將一元線性回歸分析、自然正交函數法（ eof ）和逐步回歸方法結合起來，建立了南京感冒以及金華的上呼吸道感染、腦出血和腦梗塞的發病指數預報模型。並將模型結果與逐步回歸法建立的模型進行比較。 -
After that, the paper makes a relatively profound study analysis of the structure calculation and error adjust forecast technique used in pc rigid frame bridges construction monitor and control, and comprehensive analyzes of the influence factors in building the bridges, based on the engineering practice
本論文的其後部分主要是從工程實際出發，對預應力混凝土剛構橋施工過程線形預拱度控制的結構計算分析和誤差調整預測方面作了較為深入的研究，對預應力混凝土剛構橋施工控制過程的影響因素作了全面的分析。 -
Also, a predictive model is established with method of ssa - mem, which can be used to predict monthly mean temperature of the first half year in heilongjiang province. rms error of these two methods are both less than climatological forecast ' s, especially, independent sample is adopted in ssa - mem method
並利用ssa - mem方法建立可用於黑龍江氣溫的年度預報模型，這兩種方法的預報均方根誤差均小於氣候預報的均方根誤差，而且ssa - mem方法是獨立樣本試驗。 -
Further analysis on the model forecast residuals indicate that the residual time series does not follow a normal distribution but rather exhibits non - gaussianity ; similarly too, the existence of persistent pattern in the error / residual structure is discernibly evident
對模型預報殘差進一步分析可知，殘差的時間序列並不服從正態分佈，而是呈現出了逆高斯分佈。同樣，在誤差/殘差結構中存在著非常明顯的固定模式。 -
Forecast of error coefficients based on the matrix splitting algorithm of least squares support vector machine for gyroscope
基於最小二乘支撐矢量機矩陣分割演算法的陀螺儀誤差系數預測 -
When the load of agriculture and illume is forecasted, the load is decomposed into stationary terms that is not related to meteorologic factors and random term that is related to meteorologic factors by use of wavelet analysis. because the forecasting accuracy of stationary term is higher and the amplitude of random term, although it is difficult to forecast, is smaller, so the impact of forecasting error bringing about by random factors on final forecasting result is weakened
在預測不同行業的負荷時，利用小波分析的方法對農業和照明負荷序列進行分解，然後將頻率較低的部分視為與氣象因素無關的穩定項進行處理，將頻率較高的部分視為與氣象因素相關的隨機項進行處理，由於穩定項預測精度高，隨機項雖較難預測但幅值較小，因此削弱了隨機因素帶來的預測誤差對最終結果的影響。 -
The purposes of this technical reform are to raise the measurement accuracy of the miss - targets and to improve the system error of the axis, hence increase the space pointing accuracy of satellites. it can offer a measurement means for high accuracy measurement orbit, forecast and method research on the space targets
本項改造提高了脫靶量的測量精度和減小了軸系的系統偏差，從而提高衛星的空間定位精度，為空間目標高精度測軌預報和方法研究提供了測量手段。 -
In this dissertation, put forward a practical modal to forecast the probability of human error and analyze the effect of reliability as a result of human error based on the analysis of cause and effect of human error during construction ; put forward the model of considering the effect of human error and the practically method of calculate fuzzy - random reliability considering the effect of human error ; popularize the theory of traditional random reliability to the theory of fuzzy - random reliability, and discuss the theory of reliability of the whole - course in structural life ; put forward the countermeasure to reduce human error according to the fact
本文通過對施工過程中人為錯誤的因果分析，建立了比較實用的人誤概率預測模型，分析了施工過程中人為錯誤對結構可靠度的影響；提出了考慮人為錯誤影響的結構模糊隨機可靠度的模型和實用的計算方法，將傳統的隨機可靠度理論推廣到模糊隨機可靠度理論；還探討了結構生命全過程可靠度理論，並結合實際情況提出了減少人為錯誤的對策。 -
In this pape, a bp networks is founded to show the relationship of the key control data and the location of cables on span arch construction. form the stable network through the self - study, and use this networks to forecast the location of cables. this method avoid the error produced by man - made
本文利用bp網路來建立施工中的關鍵控制數據（關鍵受力點的受力大小、扣索控制點標高值、扣索受力最大及最小值等）與扣索及拱肋連接點之間的映射關系，通過網路的自學習功能得到穩定的網路。 -
Neural network method was adopted here to build an updating model which predicts the error used in forecast error correction. proper improvements for bp neural network were also made according to the actual situation
在實時校正中運用神經網路方法進行誤差預報，並根據研究的具體情況對bp神經網路進行了適當的改進。 -
In addition, the characteristic of outlier in the reservoir inflow is analyzed and the theory of robust estimation is introduced into the forecast of reservoir inflow and real - time error correction of it. the robust system can prevent outlier and extreme error from influencing correction efficiency, so as to improve the stability of correction results
分析水庫入庫實測流量中粗差的特點，把抗差理論與方法引入水庫入庫洪水預報和誤差實時修正中，研究了具有抗差特性的洪水預報實時修正方法，以抗禦粗差和極值誤差對修正結果的影響，增強了修正結果的穩定性。 -
In this paper, we analyze the statistic characters of time - delay in detail, and put forward to adopt elman nn to forecast time - delay intelligently, design appropriate compensator based on adaptive smith forecast theory. the experiment results prove that this method can improve the forecast accuracy and system ' s dynamic performance. in the application of real time data transmission, forward error correction ( fec ) is a good method to resume the lost data
針對這個問題本文進行了詳盡的統計特性分析，並且提出採用elman動態神經網路結構對網路時延進行智能預測，並根據自適應smith預估補償控制原理設計合適的時延補償器，並且應用於基於web的二階水位控制系統中，實驗結果證明了採用此方法可以提高預測精度，使時延補償器適應時延變化的動態性更強，從而在保證系統穩定性的基礎上，西安理工大學碩士學位論文提高系統的時延補償精度。 -
Quantitative analysis is the second module in the stock price forecast system ( the first module is solving the problem of what kind of stock should be chosen. ). the stock price forecast model has been built by utilizing mathematic methods and cad. in this model the error is also be controlled within the specific limits
定量分析在定性分析的基礎上（即解決了買什麼樣的股票問題后） ，利用數學建模、計算機輔助設計對股票價位進行預測，並將預測的誤差控制在一定范圍內，從而對先前定性分析得到的結論作進一步驗證。 -
So it is rough this method to forecast, which educes approximate forecasting value and the error is bigger comparatively. this method ca n ' t be satisfied when calling for good precision
因此，這種方法預測比較粗糙，只能在宏觀上有個大致的預測，預測誤差比較大，對于精度要求比較高的很難滿足。
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