信息融合
融合
计算机科学
地质学
人工智能
哲学
语言学
出处
期刊:CRC Press eBooks
[Informa]
日期:2017-04-24
卷期号:: 94-101
标识
DOI:10.1201/9781315226187-17
摘要
Geological comprehensive prediction of tunnel is a very complicated process and the geological predicting workers have to face large amounts of geological materials and field data, which should be organized and analyzed effectively to obtain correct predicting results. Recent years have seen some comprehensive predicting models put forward (Ge et al. 2010, Xu et al. 2013, Xu et al. 2011, Yuan et al. 2011), which can integrate multiaspect information and have achieved good results in some engineering cases. There are still some shortcomings and limitations in these studies; for instance, the fuzzy evaluation method in the existing comprehensive predicting model mainly reflects the consistency but no clear description of conflict between each evaluation index. Meanwhile, as a complicated engineering system, the geological prediction of tunnel produces several uncertainties, but the current fuzzy evaluation methods are difficult to fully reflect the uncertain characteristics of the information.
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