本文提出了一种基于核岭回归和粒子滤波的室内移动目标追踪算法,该算法在离线阶段采用核岭回归方法提取传感器之间的距离与RSSI(Received Signal Strength Indicator)信号值之间的非线性关系,从而训练出一种非线性回归距离模型;在线追...本文提出了一种基于核岭回归和粒子滤波的室内移动目标追踪算法,该算法在离线阶段采用核岭回归方法提取传感器之间的距离与RSSI(Received Signal Strength Indicator)信号值之间的非线性关系,从而训练出一种非线性回归距离模型;在线追踪阶段,利用非线性回归模型和粒子滤波算法实现室内移动目标的定位和追踪。本文在典型的室内办公环境下进行实验,并通过MATLAB对实测数据进行仿真。实验结果表明,相比WKNN算法和KF算法,本文所提出的算法能到达更好的定位精度,误差均值为1.2743 m。展开更多
Classical density functional theory is used to study the associating Lennard Jones fluids in contact with spherical hard wall of different curvature radii.The interfacial properties including contact density and fluid...Classical density functional theory is used to study the associating Lennard Jones fluids in contact with spherical hard wall of different curvature radii.The interfacial properties including contact density and fluid-solid intcrfacial tension are investigated.The influences of associating energy,curvature of hard wall and the hulk density of fluids on these properties are analyzed in detail.The results may provide helpful clues to understand the interfacial properties of other complex fluids.展开更多
文摘本文提出了一种基于核岭回归和粒子滤波的室内移动目标追踪算法,该算法在离线阶段采用核岭回归方法提取传感器之间的距离与RSSI(Received Signal Strength Indicator)信号值之间的非线性关系,从而训练出一种非线性回归距离模型;在线追踪阶段,利用非线性回归模型和粒子滤波算法实现室内移动目标的定位和追踪。本文在典型的室内办公环境下进行实验,并通过MATLAB对实测数据进行仿真。实验结果表明,相比WKNN算法和KF算法,本文所提出的算法能到达更好的定位精度,误差均值为1.2743 m。
基金Supported by the North China Electric Power University Campus Foundation under Grant No 200911036.
文摘Classical density functional theory is used to study the associating Lennard Jones fluids in contact with spherical hard wall of different curvature radii.The interfacial properties including contact density and fluid-solid intcrfacial tension are investigated.The influences of associating energy,curvature of hard wall and the hulk density of fluids on these properties are analyzed in detail.The results may provide helpful clues to understand the interfacial properties of other complex fluids.