为了加速速度和压力迭代的收敛性成功地引入了质量流量校正法。
The method of mass flux correction is introduced with success in order to accelerate convergence in iteration of velocity and pressure calculation.
实验结果表明，该算法不仅具有较好的全局收敛性，而且具有较高的加速比。
The experimental results show that the new algorithm has better global convergence, and also has higher speed-up ratio.
仿真结果表明，改进的BP算法可显著加速网络训练速度，学习过程具有较好的收敛性和较强的鲁棒性。
The simulation results show the presented quick training algorithm can speed up the learning process of MLP, and improve the learning properties on convergence and robust performance.
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