GM（0,N）模型在河流径流量预测中的应用

河流径流量的预测对水资源的优化调度管理具有重要的意义,传统的预测方法中原始数据的随机性对预测精度具有很大的影响。对GM（0,N）模型进行了研究,建立了以河流径流量为系统特征数据序列,年平均降水量和年平均饱和差为相关因素序列的GM（0,3）模型。通过模型预测数据和实测数据的对比,说明了GM（0,N）模型具有较好预测效果;同时,为了证明GM（0,N）模型的优点,对比了其预测结果与线性回归预测模型的结果。     

A new improvement of TCP based on adaptive filtering

On the basis of studying the standard TCP retransmission mechanism,this paper proposes a method to adopt the theory of adaptive filtering in the field for the estimation of round trip time (RTT).Then t...     

Motion feature descriptor based moving objects segmentation

A novel moving objects segmentation method is proposed in this paper.A modified three dimensional recursive search (3DRS) algorithm is used in order to obtain motion information accurately.A motion fea...     

Context-aware end-to-end QoS diagnosis and guarantee based on Bayesian network

A systematic approach for end-to-end QoS qualitative diagnosis and quantitative guarantee is proposed to support quality of service (QoS) management on current Internet.An automatic unwatched discretiz...     

MAP based blocking artifact reduction for DCT domain distributed video coding

This paper proposes a maximum a posteriori (MAP) based blocking artifact reduction algorithm for discrete cosine transform (DCT) domain distributed video coding,in which the SI and the initial reconstr...