计算机科学 ›› 2018, Vol. 45 ›› Issue (10): 59-63.doi: 10.11896/j.issn.1002-137X.2018.10.012
• 2018 年中国粒计算与知识发现学术会议 • 上一篇 下一篇
陈丽芳1, 代琪1, 付其峰2
CHEN Li-fang1, DAI Qi1, FU Qi-feng2
摘要: 在数据智能处理中属性重要度差异很大且具有高度非线性的特征,在这种情况下直接应用机器学习进行建模处理往往很难获得问题的有效解。针对此问题,文中探索了基于粒计算的属性重要度的排序方法且结合排序结果应用二元关系实现粒层划分算法;应用极限学习机对不同划分获得的粒层空间进行学习,进而对不同粒层空间的学习结果进行对比分析,从而获得最优划分与粒层;此外,将提出的粒度极限学习机模型应用于空气质量的预报问题,不仅加快了预报速度,而且获得的结果与实际预测高度吻合,实证了粒度极限学习机模型的有效性和可靠性。
中图分类号:
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