预测精度

实践结果表明，Usher模型比Logistic模型和Gompertz模型具有同等或更高的预测精度。

The practical results show that in comparsion with the Logistic Model and Gompertz Model , the Usher Model is of an identical or higher forecast accuracy .

实验表明，该方法的时间序列预测精度高于任意个体RBF的预测精度，将该方法应用于水环境水质预测，获得了较好的实际应用效果。

Through the experiment , the result shows that the forecast accuracy of the RBF neural network integration method is higher than any individual in the forecast accuracy of RBF and the method get better application effect when using the method in the water quality forecast of water environment .

总体来说，季节性时序模型的模拟和预测精度较高。

The time sequence model synthetically reflects trends of groundwater level .

此方法是根据跟踪信号不断调整加权系数，以此提高预测精度

AWES adjust the smoothing factor continuously according to anterior prediction errors .

此方法避免了网络陷入过饱和，提高了网络的收敛速度和预测精度，优于经典的BP算法。

The improved method avoids over-fitting of the network , improves convergence speed and predictive accuracy of the network .

同时，运用交叉验证法优化SVM的惩罚参数和核参数，有效提高了预测精度。

And using cross validation to optimize the SVM penalty parameter and kernel parameter , effectively improve the prediction accuracy .

提高预测精度的ELMAN和SOM神经网络组合

Using combination of ELMAN and SOM neural networks to enhance prediction precision

将等维递推和自适应的思想引入改进GM（1,1）模型，可进一步提高该模型的预测精度和实用性。

Prediction accuracy and practicability can be further improved by use of equal-dimension recurrence and self-adapting in GM ( 1,1 ) model .

为了提高Web流量的预测精度，提出一种基于小波、神经网络和自回归的组合预测方法。

For improving the prediction accuracy of Web traffic , a novel combination prediction method was proposed based on the integration of the wavelet , neural network and the auto-regression ( AR ) .

实验结果表明，所提算法提高了SVM分类器的预测精度，缩短了训练时间。

Experiment results show that the presented algorithm can improve the prediction accuracy and reduce the training time of support vector machine .

利用这种组合算法得到的相似日作为SVM的输入提高了SVM方法的预测精度。

Use the similar days got from this combination as the input of SVM and thus improve the prediction accuracy of SVM .

实测数据检验表明，DBP模型预测精度较高。

The testing result indicates the prediction precision of DBP model is relatively high .

并利用PLS法分析上下颌参数，对距离类数据建立了具有较高预测精度的回归模型。

Using PLS method to analyze mandibula and maxilla , establish regression model to forecast parameters accurately .

实例证明了组合模型的预测精度高于单独的GM（1,1）模型，可以用于公路客运量预测。

Practical instance proves the estimation precision of combined model is higher than individual GM ( 1,1 ), and can be used in road passenger traffic estimation .

结果表明，该模型具有调节参数少、运算速度快、结果稳定、预测精度高等优点，可以根据燃煤特性以及各操作参数准确预报锅炉在不同工况下的NOx排放和效率。

The model can predict the NOx emission and boiler efficiency simultaneously with fast calculating speed and high accuracy under various operating conditions .

通过与传统的季节ARIMA模型相比较，提出的改进模型能够很好地提高预测精度。

The results demonstrate that the proposed model can improve the prediction accuracy noticeably compared with Seasonal ARIMA model .

当顾客满意度指数测评指标和测量成分较多时，PLS回归建模方法和模糊综合评判方法都存在简化测量成分而造成信息损失和难以估计预测精度的问题。

When there is too many evaluation targets and ingredients , the above methods will lead to information loss and sharply accuracy decrease .

与传统的BP算法相比较，该算法的预测精度较高，计算结果稳定性好，收敛速度快。

According to the comparison between the prediction results and the conventional BP algorithm , it can be seen that this algorithm has advantages of high prediction accuracy , fine stability and fast convergence speed .

针对非均匀分布的样本数据，提出了采用局部加权LS-SVM算法进行在线建模来提高预测精度。

For non-uniformly distributed training data , a local weighted LS-SVM method for the online modeling of continuous process is proposed .

GARCH模型的预测精度有限，但是对于中、短期的收益率还是有较好的预测能力。

The forecasting precision of GARCH model is limited , but it still has a good ability in short and middle forecasting .

为了提高变形抗力预测精度，针对传统热轧变形抗力模型的固有缺陷，提出一种将动态BP神经网络与数学模型相结合的新方法。

In view of intrinsic imperfection of traditional models of flow stress of steels with hot rolling , a new method combining dynamic BP networks with mathematical models is proposed to improve precision of flow stress prediction .

仿真结果表明：固定尺度最小二乘支持向量机在训练各种样本数据集时，有效地避开了LS-SVM中的稀疏性问题，且训练速度快，同时具有良好的预测精度。

The simulation results indicate that fixed size LS_ - SVM shortens the training time enormously and possesses good predicting precision on different datasets .

改进SRK方程提高正构烷烃饱和蒸气压和液体体积预测精度

Modified SRK equation of state to improve prediction of saturated vapor pressures and saturated volumes of alkanes

采用修正参数修正B3模型，以此来提高该模型的预测精度。

And also B3 prediction model for creep was updated by changing some parameters of the model to enhance the accuracy of prediction .

在改进B-P算法、提高B-P算法预测精度的基础上，对内蒙古粮食总产量进行了预测。

This paper forecasted the grain gross output of Inner Mongolia by improved back propagation algorithm with high forecast precision .

通过实例的分析计算，证明改进的模型具有良好的预测精度，满足工程实际需要，拓广了GM（1,1）模型的适用范围。

The results of cases prove that the proved model is reliable , and the precision of fit and prediction can meet engineering need . So it extend the application domain of GM ( 1,1 ) model .

因此，建议在欠平衡钻井设计中应用预测精度较高的Ansari方法。

So the Ansari Method is recommended to use in UBD design because of its higher prediction accuracy .

将与购买意愿有显著相关性的13个因素作为自变量，购买意愿作为因变量，建立Logistic回归模型，预测精度为80.8%。

The research use the 13 factors that are significant correlated with intention to purchase as independent variables , and intention to purchase as dependent variables , builds up the logistic regression model , with a prediction accuracy of 80.8 % .

工业实例表明LS-SVM所建模型的预测精度较高，能满足实际工业应用的需求。

The simulation results by use of real industrial data show that the soft sensors based on LS-SVM is accurate in prediction , so they are suitable to practical application .

灰色摆动序列经过动态指数变换具有灰指数特性，对变换后数据序列建立GM（1,1）可以进一步提高预测精度。

In this paper , grey wobbly sequence takes on grey exponent character by an especial dynamic exponent transformation . After that , if GM ( 1,1 ) for the transformed sequence is set up , the forecasting accuracy is improved more .