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Background We present a Support Vector Machine (SVM) approach to the localization of hazardous particulate releases in an urban area using features constructed only from measurements obtained from a network of sensors. Results We find high levels of localization accuracy when a reasonable number of noisy sensors are deployed within the environment. We also compare SVM source localization...
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