Multiple Regression Analysis for Arsenic Removal from Groundwater
Leila Suzuki
Corresponding
Nanyang Technological University
Hiroshi Liu
University of Cape Town
Abstract
The shift towards cleaner technologies has renewed attention on arsenic removal from groundwater within biomedical instrumentation. The proposed framework combined scanning electron microscopy with laboratory measurements to improve predictive accuracy. The proposed algorithm converged reliably within 4 iterations for every case that was tested. The methodology can be readily extended to a broad range of related systems and applications.
Keywords:
arsenic removal from groundwaterscanning electron microscopysoil liquefactionphotocatalysis
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