首先，为了去除测量产生的噪声和误差，引入高斯核函数为每个采样点加权；
To filter out the noise and error arising out of various physical measurement processes and limitations of the acquisition technology, a Gaussian weight is assigned to each point acquired.
针对混沌时间序列的最近邻域预测法，提出了改进的最近邻域点优化选择方法和加权一阶局域线性预测法。
Optimal choice method of the nearest neighboring points and adding weight one-rank local region method is introduced on the nearest neighboring forecasting method of chaotic time series.
最终推出了任意无向加权图K点连通最小扩充的模拟退火算法。
Finally, this paper gave simulated annealing algorithm for K-vertex-connected minimal augmentation on arbitrary undirected weighted graph.
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