在传感器网络中,多个传感器对于同一目标的识别结果经常会发生冲突.本文采用基于D em pster-Shafer证据推理理论的数据融合方法来解决这一问题.然而,采用D-S证据组合公式计算融合结果,计算量过于巨大,对处理能力有限的感知结点来说负担...在传感器网络中,多个传感器对于同一目标的识别结果经常会发生冲突.本文采用基于D em pster-Shafer证据推理理论的数据融合方法来解决这一问题.然而,采用D-S证据组合公式计算融合结果,计算量过于巨大,对处理能力有限的感知结点来说负担过重,此外,计算所造成的延时也将严重影响系统的实时性和同步性.本文提出了一个基于矩阵分析的快速融合算法,该算法采用了D-S证据理论的思想,计算得到的融合结果与D-S证据组合公式计算得到的融合结果相同.本文用数学归纳法证明了这一结论.经过模拟实验验证,和直接采用D-S证据组合公式相比,该算法的计算量和所需的计算时间明显减少.展开更多
Firstly, the research progress of grey model GM （1,1） is summarized, which is divided into three development stages： assimilation, alienation and melting stages. Then, the matrix analysis theory is used to study th...Firstly, the research progress of grey model GM （1,1） is summarized, which is divided into three development stages： assimilation, alienation and melting stages. Then, the matrix analysis theory is used to study the modeling mechanism of GM （1,1）, which decomposes the modeling data matrix into raw data transformation matrix, accumulated generating operation matrix and background value selection matrix. The changes of these three matrices are the essential reasons affecting the modeling and the accuracy of GM （1,1）. Finally, the paper proposes a generalization grey model GGM （1,1）, which is a extended form of GM （1,1） and also a unified form of model GM （1,1）, model GM （1,1,α）, stage grey model, hopping grey model, generalized accumulated model, strengthening operator model, weakening operator model and unequal interval model. And the theory and practical significance of the extended model is analyzed.展开更多
文摘在传感器网络中,多个传感器对于同一目标的识别结果经常会发生冲突.本文采用基于D em pster-Shafer证据推理理论的数据融合方法来解决这一问题.然而,采用D-S证据组合公式计算融合结果,计算量过于巨大,对处理能力有限的感知结点来说负担过重,此外,计算所造成的延时也将严重影响系统的实时性和同步性.本文提出了一个基于矩阵分析的快速融合算法,该算法采用了D-S证据理论的思想,计算得到的融合结果与D-S证据组合公式计算得到的融合结果相同.本文用数学归纳法证明了这一结论.经过模拟实验验证,和直接采用D-S证据组合公式相比,该算法的计算量和所需的计算时间明显减少.
基金supported by the National Natural Science Foundation of China(70971103)the Specialized Research Fund for the Doctora Program of Higher Education(20120143110001)
文摘Firstly, the research progress of grey model GM （1,1） is summarized, which is divided into three development stages： assimilation, alienation and melting stages. Then, the matrix analysis theory is used to study the modeling mechanism of GM （1,1）, which decomposes the modeling data matrix into raw data transformation matrix, accumulated generating operation matrix and background value selection matrix. The changes of these three matrices are the essential reasons affecting the modeling and the accuracy of GM （1,1）. Finally, the paper proposes a generalization grey model GGM （1,1）, which is a extended form of GM （1,1） and also a unified form of model GM （1,1）, model GM （1,1,α）, stage grey model, hopping grey model, generalized accumulated model, strengthening operator model, weakening operator model and unequal interval model. And the theory and practical significance of the extended model is analyzed.
