| 1. | Traffic prediction based on genetic - neural network
神经网络的交通量预测 |
| 2. | Vbr mpeg video traffic prediction modeling based on
视频流量预测模型 |
| 3. | Improvement of time - series method for short - term traffic prediction
短时段交通预测时间序列方法的改进 |
| 4. | The time - series method has come into wide use in short - term traffic prediction
摘要时间序列方法在短时交通预测中应用广泛。 |
| 5. | Modeling and analysis of network traffic prediction using autoregression and support vector machine based on byte length in data packets
引入非线性小波基函数构造支持向量机 |
| 6. | Finally , the prediction method of network traffic is proposed . simulations show that farima ( p , d , q ) is effective for long - range dependent network traffic prediction
最后,根据已经得到的farima ( p , d , q )模型,提出了预测未来业务流流量的方法,并通过实际业务量进行了验证。 |
| 7. | Then the article summarize the traffic characteristic of existing traditional network , and analysis the existing network traffic prediction model and it ’ s advantage and disadvantage
总结了现有传统网络流量特征,归纳分析了现有的网络流量预测模型,并分析了现有预测模型的优缺点。 |
| 8. | Based on the correlation structure of real - time variable bit rate video traffic , this paper proposed a dynamic bandwidth allocation ( dba ) algorithm with adaptive linear traffic prediction in ethernet passive optical network ( epon )
摘要根据视频数据流的长程相关性特点，提出一种以太无源光网络中面向实时可变比特率视频的动态带宽分配算法。 |
| 9. | Secondly , bayesian theory is applied to the risk evaluation of the traffic prediction . then , the future inference can be gained from the experience data and the specimen data by the theory ; meanwhile , the predicted result can be modified constantly with the increase of the specimen
再者，将贝叶斯推断理论应用于公路建设项目的交通量预测风险研究，这种预测方法能够根据先验信息和样本信息做出后验的推断，并能随着样本的增加不断修正预测结果。 |
| 10. | In the other way , traffic models play an important role in network traffic prediction and design . a good traffic model can help us to keep the status of the network and to control sudden evens in the net work . usually different kinds of the models have
目前有许多的研究者对网络流量建立不同的数学模型,针对不同的应用有着不同的功能,如对网络作短期预测的数学模型,以及时的控制网络的突发风暴,对网络作长期预测的数学模型,有利于网络的长期维护和长远的发展。 |
