Mathematical modeling of groundwater anomaly detection
Public concerns about groundwater quality have increased in recent years due to the massive exploitation of shale gas through hydraulic fracturing which raises the risk of groundwater contamination. Groundwater monitoring can fill the gap between the public fears and the industrial production. However, the studies of groundwater anomaly detection are still insufficient. The complicated sequential data patterns generated from subsurface water environment bring many challenges that need comprehensive modeling techniques in mathematics, statistics and machine learning for effective solutions. In ...
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