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   average prediction 的翻译结果: 查询用时:0.218秒
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average prediction
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  预测平均
     The average prediction errors of MON and RON are 0.192 and 0. 178 respectively.
     马达法辛烷值与研究法辛烷值预测平均误差分别为0.192,0.178。
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     For σA promoters,the average prediction accuracies are 90.7%;
     对σA启动子的预测,平均正确率达到了90.7%;
短句来源
     for other σfactor promoters,the average prediction accuracies also hi gher than 80%.
     对几种其它σ因子启动子的预测,平均正确率也超过了80%.
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     The average prediction error by this model is 0.959% for the refractive index of 95 amorphous homopolymers.
     由该模型对95个聚合物的折光率进行预测,平均相对误差为0.959%.
短句来源
     The average prediction error of motor octane number and research octane number were 0.2 and 0.18 respectively.
     马达法辛烷值预测平均误差为0.20; 研究法辛烷值预测平均误差为0.18。
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  平均预报
     The cross experiments indicated that the average matching relative error and the average prediction relative error of this model, was 0.0063% and 0.1210% respectively. The model was applied to predict the concentration of CO_2 in the exit of purifying column.
     交叉验证表明,所建模型平均拟合相对误差为0.0063%,平均预报相对误差为0.1210%,该模型可用于提纯塔出口CO2浓度的预测。
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  平均预测
     If the fixed-length pattern was taken as 10 amino acids,the average prediction accuracies of the"1041type" were 83.1% and 79.8% by the 3-cross validation test and jack-knife test,respectively.
     当序列模式固定长取10个氨基酸残基时,对“1041”序列模式3交叉检验的平均预测精度达到83.1%,jack-knife检验的平均预测精度达到79.8%。
短句来源
     The compositions of amino acids and twin amino acids were chosen as the information parameters of the amino acids sequences. The prediction results show that average prediction accuracies of the"822type"for fixed-length pattern with 8 amino acids were 78.1% and 76.7% by the 3-cross validation test and jack-knife test,respectively.
     从蛋白质一级序列出发,以氨基酸(20种氨基酸加一个空位)和其紧邻关联共同为参数,当序列模式固定长取8个氨基酸残基时,对“822”序列模式3交叉检验的平均预测精度达到78.1%,jack-knife检验的平均预测精度达到76.7%;
短句来源
     Application of Moving and Average Prediction Method to Decision Supporting in Embankment Construction
     移动平均预测在堤防施工决策中的应用研究
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     By using MIMO to predict a real example of case the result shows,the error of average prediction is small than 0.37%,the accurate degree raised 2.91 times than moving average method,raised 4.28 times than other analysis method.
     通过MIMO对一个案例进行实际预测 ,结果表明 :平均预测误差均小于 0 .37% ,比移动平均法精度提高了 2 .91倍 ,比回归分析提高了 4.2 8倍。
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     Relation curve of average prediction error versus neighbors' number is calculated.
     计算了辐射噪声序列的平均预测误差与邻域大小的关系曲线,从曲线的类型可判断辐射噪声序列的线性性,并得到合适的预测函数类型及参数。
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  “average prediction”译为未确定词的双语例句
     Finally,the integrated prediction was taken based on the above two prediction results,whose weights were calculated by its log-logistic probability density and average prediction error was reduced to 21.20%.
     最后,确定近海水质数据符合log-logistic的概率密度函数,提出将上述两种预测结果的概率密度作为其组合权重的近海水质组合预测方法,平均误差降低为21.20%.
短句来源
     An integrated improvement on the force model has been made in the present investigation, including model structure, measuring methods and sub-routine of three most important variables-flow stress, contact length and friction coefficient. A high accuracy force model for cold rolling is constructed with average prediction deviation <5% before ANN treatment.
     本研究在模型结构和3个最重要自变量——材料的流变应力,弹塑性接触弧长和界面摩擦系数——的测定方法和计算模型上进行了全面改进和更新,建立起高精度冷轧轧制力数学模型,将人工神经网络(ANN)处理前的预报精度提高到了5%以内.
     The experimental results show that the mapping between the colorimetric space and the recipe space can be realized by the multi-layer BP neural networks, and the average prediction error for 64 training samples is less than 1 unit of CIELAB color difference.
     实验结果表明,基于多隐层BP网的模型可以实现粉末涂料样品的配方浓度空间与标准三刺激值颜色空间的相互映射,对64个节点的平均训练精度达到了1个CIELAB色差单位。
短句来源
     By the means of the extra-smoothing average prediction, the dissertation attempts topredict the tendency of climatechanges in the coming 5 or 9 years from 1995. By applyingregression analysis and numericalvalue simulation in Excel and SPSS, the author sums up thefluctuation tendency of the grainyield in Yunnan Province in the past 45 years.
     并利用滑动平均外推预测法,预测了云南未来5~9年的气候变化趋势。 借助EXCEL、SPSS中的回归分析及数值模拟方法,总结了过去45年来云南粮食产量的波动趋势。
短句来源
     The average prediction accuracies for "non-coding" promoters and "coding" promoters are 86.7% and 82.4%,respectively. The results indicate that our algorithm outperforms most of the existing approaches based on several performance measurements.
     对位于非编码区的启动子,平均正确率达到了86.7%,明显优于其它算法; 对位于编码区内部的启动子,平均正确率也达到了82.4%。
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  average prediction
Numerical experiments are carried out for day-to-day prediction and temporal average prediction.
      
Average prediction errors for serum trough concentrations were 48.3% for neural networks and 59.0% for NONMEM.
      
While inferred Bayesian trees demonstrate low average prediction error rates, there is reason to believe that error rates will be higher for those leaves with few training examples.
      
Both the method and the continuous data set were tested and tuned to obtain the minimum of a normalized average prediction error (E) during the last millennium using several past millennia as a training data set.
      
With a genetic algorithm it was possible to construct hypothetical subsite maps (with inhibition constants) that gave further improvements in the average prediction for all saccharides.
      
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The self-tuning technology is a new branch of the mordern control theory. In this paper we try to present the application of the self tuning prediction approach to the power system load forecasting. After a short introduction of its basic principle, a new power system load model is proposed in the paper, as it is the key-point of the forecasting problem. Simulation with a set of real power system ioad data shows that the average prediction error is about 3.24%. It also demonstrates that the approach has...

The self-tuning technology is a new branch of the mordern control theory. In this paper we try to present the application of the self tuning prediction approach to the power system load forecasting. After a short introduction of its basic principle, a new power system load model is proposed in the paper, as it is the key-point of the forecasting problem. Simulation with a set of real power system ioad data shows that the average prediction error is about 3.24%. It also demonstrates that the approach has a number of advantages such as simple algorithm, good convergence, etc.. It is considered that the approach is applicable while further work is needed for its practical application.

自校正技术是现代控制理论中的一个新分支。本文的目的是要将自校正预测技术应用于电力系统负荷预报。为此,首先简要地叙述了自校正预测器的基本原理,然后根据电力负荷序列的特性提出一个新的负荷模型。少量试验结果给出预报误差均值为3.24%,整个过程体现了自校正预测器算法简单,收敛性好等优点,该方法是可行的。

The correlations of power consumption (P_g) in aerated agitated vessels were analyzed. It was shown that the aeration number N_q, the most prominent factor of determining P_g, should be amended with the gas recirculation coefficient α,otherwise a prediction error more than 40% would be caused before large cavities were formed. A correlation was obtained for predicting P_g,which was more reliable and could be used under more conditions: For more than 150 data under kinds of conditions from threeliteratures,...

The correlations of power consumption (P_g) in aerated agitated vessels were analyzed. It was shown that the aeration number N_q, the most prominent factor of determining P_g, should be amended with the gas recirculation coefficient α,otherwise a prediction error more than 40% would be caused before large cavities were formed. A correlation was obtained for predicting P_g,which was more reliable and could be used under more conditions: For more than 150 data under kinds of conditions from threeliteratures, the average prediction error from the above correlation was only 9.5%, and the largest error was less than 20%.

评估了通气式搅拌釜较有代表性的搅拌功耗关联式,指出大气穴形成之前,气体再循环将导致关联式预测值偏离实际值40%以上。用气体再循环系数对关联式进行修正,可得到适用于装有涡轮搅拌器的低粘体系的新的搅拌功耗关联式:当G≤2.54时,Pg/P0=0.71G-0.80;当G>2.54时,Pg/P0=1.0;式中,G=(N(p0)/N(p0))0.6(d/D)0.15Fr0.05[(1+α)Nq]-0.25,α=0.335(Np0/Np0)1.5(d/D)3.0Fr0.6Nq-1.0。 对3篇文献中的150多组功耗数据(N=2~15s-1,QG<4.5×10-3m3/s,d/D=0.15~0.4,nb=6~18,Np0=5~12)进行预测,平均偏差仅为9.5%,最大偏差小于20%。

The performance of codebooks designed for LSP with GLA and stochastic relaxation(SR) algorithm is investigated, and the features of two algorithms are discussed. The first order moving average prediction residual vectors of the mean removing LSP is used as the training sequence. The SR algorithm applied is a simplified SR algorithm for the decoder perturbation. The traditional conclusion is that SR saves GLA 1 bit per vector index. The experiment shows that the conclusion is right for a small amount...

The performance of codebooks designed for LSP with GLA and stochastic relaxation(SR) algorithm is investigated, and the features of two algorithms are discussed. The first order moving average prediction residual vectors of the mean removing LSP is used as the training sequence. The SR algorithm applied is a simplified SR algorithm for the decoder perturbation. The traditional conclusion is that SR saves GLA 1 bit per vector index. The experiment shows that the conclusion is right for a small amount of training sequence, but the difference in their performances is slight for a large amount of training sequence. The SNR improvement of codebook designed with SR algorithm is little when a LSP quantizer is designed.

研究 GL A算法和随机松驰算法设计的线谱对码本性能以及两种算法的特点 .训练数据采用了去均值和一阶滑动平均模型预测的误差信号 ,随机松驰算法选用简化的解码器扰动算法 .传统观点认为随机松弛算法比 GL A算法每矢量索引少用 1bit.实验结果表明 ,在小训练数据量时的确如此 ,但在大数据量时它们的性能相差不大 .在线谱对的码本设计中 ,随机松驰算法设计的码本信噪比提高很小

 
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