数据流定性化方法研究
RESEARCH OF FORMING THE QUALITATIVE TREND FROM THE MEASUREMENT STREAM
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摘要: 数据流定性化处理,是在考虑噪声影响的情况下,对数据流进行处理,最终将数据流化分为单调变化的区段.这是定性仿真应用中的一个关键问题.本文在分析基于线性最小方差拟合的数据流定性化方法的基础上,改进其定性核心函数.提出了基于偏度系数的数据流定性化方法.并通过具体数据分析,证明了该方法的有效性.Abstract: The qualitative trend is generated through a process which breaks the measurement stream into monotonic segments. It is important for the applications of qualitative simulation. After analyzed the method which using linear least-squared fit, we modified the qualitative kernel function and presented the method which using deflecting modulus. In the end of the article, we demonstrated the effectiveness of the method.