基于插值梯形模糊信息粒化的瓦斯浓度趋势预测

针对现有模糊信息粒化方法构建的高层信息粒不能完全包含底层数据信息、预测时间范围受限等问题,提出了一种插值梯形模糊信息粒化方法来预测瓦斯浓度趋势。对原始瓦斯浓度时间序列进行离散化形成若干子序列,计算每个子序列窗口的最大值与最小值形成梯形上沿的边界,通过对每个子序列窗口数据进行插值计算,形成新的瓦斯浓度时间序列窗口,对新的瓦斯浓度时间序列窗口采用数据遍历寻优的方式计算梯形下沿的边界,进而形成瓦斯浓度粒化区间序列。针对现有评价方法无法准确评价信息粒化效果的问题,提出了一种基于权值的粒化评价方法,通过加权均方根误差对粒化效果进行整体评价。实验结果表明,通过该方法对信息进行粒化的效果明显优于现有模糊粒化方法,并且粒化效果不随粒化窗口的增大而减小,具有较高的稳定性与鲁棒性。

Trend prediction of gas concentration based on interpolation trapezoidal fuzzy information granulation

For problems that high-level information granules constructed by existing fuzzy information granulation method cannot completely contain information in low-level data,and range of prediction time is limited,an interpolation trapezoidal fuzzy information granulation method was proposed to predict gas concentration trend.Original gas concentration time series is discretized to form sub-series,the maximum and minimum value of each sub-series window are calculated to form trapezoid-top boundary,each subseries window data is calculated by interpolation to form a new gas concentration time series window,then trapezoid-bottom boundary is calculated by use of data traversing optimization to the new gas concentration time series window,so as to form gas concentration granulation interval sequence.In view of problem that existing evaluation method cannot evaluate effect of information granulation accurately,agranulationevaluation method based on weight value was proposed,which evaluate effect of granulation through the weighted root mean square error.The experimental results shows that granulation effect of the proposed method is better than the existing fuzzy information granulation method,and the granulation effect does not decrease accompany with increase of granulation window,which has high stability and robustness.