Ack propagation and radial basis function neural network methods have been applied to water resources areas due to theirs powerful learning abilitys and many good results have been achieved.
和RBF神经网络技术以其强大的学习功能应用于水资源分类，取得了很好的效果。
By analyzing RTT's component, it is found that various transmitting delay and delayed ACK bring obvious errors in using RTT as the signal of network congestion, and affect DCA algorithms' veracity.
通过对rtt的分析发现，变化的传输延迟和延迟ack将对使用RTT指示拥塞引入明显误差，从而影响dca算法的准确性。
By analyzing RTT's component, it is found that various transmitting delay and delayed ACK bring obvious errors in using RTT as the signal of network congestion, and affect DCA algorithms' veracity.
通过对rtt的分析发现，变化的传输延迟和延迟ack将对使用RTT指示拥塞引入明显误差，从而影响dca算法的准确性。
应用推荐