This paper puts forward a seasonal neural network model to curve fitting analysis for nonlinearity and predict for the seasonal time series of outpatient amount.
本文提出一种利用季节性神经网络模型对医院门诊量进行非线性曲线拟合分析和预测。
After curve fitting analysis to the sample, obtained the practical changing law of stress concentration coefficient. Thus ANSYS can assist perfection of practical technology.
通过对样本进行曲线拟合分析，得出与实际基本一致的应力集中系数变化规律，从而证明ANSYS可以辅助实际工艺的优化。
The interpolation polynomial is applied in curve fitting for easy calculation and analysis and better representation of CT10%error curve.
采用多项式拟合曲线，可以发挥其便于计算和分析的优点，能够更好地反映电流互感器10%误差特性，使用方便。
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