By ensemble average method, the concentration distribution and error threshold of quasispecies on single peak Gaussian distributed fitness landscapes were evaluated.
利用系综平均的方法，计算了在单峰高斯分布适应面上准物种的浓度分布和误差阈。
For 481 experimental data points of 29 hydrocarbons, including high-molecular-weight hydrocarbons, the new method gives a relative average error of 3.2%.
对29种包括大分子的烃类物质，481个实验数据点，本方法的平均相对计算误差为3.2%。
To validate the independency of data, we can using the average autocorrelation function of error swatch, it can also offer thereunder to ameliorate the method of disposing data.
利用误差样本平均归一化自相关函数，可以对所抽取的数据独立性进行验证，同时为改进数据处理方法提供依据。
New dominant forecasting method and redundant measure are defined for combination forecasting method with generalized weight arithmetic average, based on error of power of p.
从P次幂误差的概念出发，提出了广义加权算术平均组合预测法新的预测方法优超和冗余度的定义。
Based on moment space theory and Gaussian approximation method, expressions of average error probability for system with multiple-access interference and white Gaussian noise environment are derived.
采用矩空间理论和高斯近似法分别得出该系统在多址干扰和白高斯噪声条件下的平均误码率表达式。
The performance of synchronization tracking using pilot is analyzed, followed by a numerical method to determine the optimal lock loop parameters to minimize average bit error rate (BER).
分析了利用导频同步跟踪的性能，以及提出了一个数值方法确定最优环路参数以最小化误码率。
The eccentric factor of 210 kinds of organic matter has been calculated by the correlation, the total average error is 2.46%, the correlation is more accurate than calculating method in literature.
计算了210种有机物的偏心因子，该关联式总平均误差为2.46%，计算准确性优于目前文献各种方法。
According to the data analysis this method is not only quick, but also the error of it is low, whose average error rate is 1.75%.
数据分析显示，该成本估算方法快速、有效而且误差较低，其平均误差为1.75%。
The analysis of measurement data error by using rear-average method was discussed. The method to count standard deviation of indirect measurement value by using rear-average method was proposed.
对用后均法进行测量数据误差分析加以探讨，提出可以用该法计算间接观测值的标准偏差。
The absolute values of the prediction error of the middle-late rice were between 0.02% and 3.77%, the average error was 1.9%. The precision was high, so the damage assessment method was feasible.
中晚稻单产灾损率的预估误差的绝对值在0.02~3.77个百分点，平均误差为1.9个百分点，预估精度较高，灾损评估方法可行。
The absolute values of the prediction error of the middle-late rice were between 0.02% and 3.77%, the average error was 1.9%. The precision was high, so the damage assessment method was feasible.
中晚稻单产灾损率的预估误差的绝对值在0.02~3.77个百分点，平均误差为1.9个百分点，预估精度较高，灾损评估方法可行。
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