一种非视距环境下基于TOA三维定位的新方法研究

为消除非视距环境对TOA三维定位带来的误差,引入演化博弈模型,以各个测量基站作为博弈局中人,为非视距环境下的TOA三维定位问题建立了一般形式的复制动态模型.研究提出了基于演化博弈的TOA定位算法,通过迭代计算消除非视距误差,获得移动端的位置估计.进一步地,针对基站位置分布明显不均的情况,在演化博弈TOA定位算法的基础上,通过构造虚拟基站和虚拟测量值,提出了基于虚拟基站的三维定位算法.实验对比显示基于演化博弈的TOA定位算法略优于经典定位算法,在基站位置分布明显不均的情况下,基于虚拟基站的三维定位算法效果较明显.     

一种基于训练数据的迭代改进核函数

为提高支持向量机性能,提出一种支持向量机核函数的迭代改进新算法.利用与数据有关的保角映射,使核函数包含了全部学习样本的信息,即核函数具有数据依赖性.基本核函数的参数可取随机初值,通过对核函数进行多次迭代改进,直至得到满意的学习效果.与传统方法相比,新算法不需要筛选核函数的参数.对一元连续函数和强地震事件的仿真计算结果表明,改进SVR(support vector regression)的学习效果优于传统方法,并且随着迭代次数的增加,学习风险下降收敛,收敛速度依赖于传统方法的基本参数和改进方法的参数.     

一种基于训练数据的迭代改进核函数

To improve performance of a support vector regression, a new method for a modified kernel function is proposed. In this method, information of all samples is included in the kernel function with conformal mapping. Thus the kernel function is data-dependent. With a random initial parameter, the kernel function is modified repeatedly until a satisfactory result is achieved. Compared with the conventional model, the improved approach does not need to select parameters of the kernel function. Sim- ulation is carried out for the one-dimension continuous function and a case of strong earthquakes. The results show that the improved approach has better learning ability and forecasting precision than the traditional model. With the increase of the iteration number, the figure of merit decreases and converges. The speed of convergence depends on the parameters used in the algorithm.