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Activity Number: 317
Type: Invited
Date/Time: Tuesday, August 8, 2006 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #305299
Title: A Neural Network Approach to Control Charts with Applications to Health Surveillance
Author(s): Benjamin M. Adams*+ and Kidakan Saithanu and J. Michael Hardin
Companies: The University of Alabama and The University of Alabama and The University of Alabama
Address: ISM Department, Tuscaloosa, AL, 35487-0226,
Keywords: neural networks ; public health surveillance ; quality control

An evaluation of multivariate monitoring scheme performances is provided. Monitoring schemes include traditional multivariate techniques, such as the MEWMA and T2 control charts, and a technique using neural networks. The neural network approach is shown to be a viable monitoring technique for complex multivariate problems, such as those found in health surveillance.

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