Analysis of Bridge Structural Health Monitoring using Random Forest Classification
Kofi Sarker
Imperial College London
Abstract
There remains a pressing need for cost-effective methods to assess bridge structural health monitoring in air pollution control. A comprehensive framework based on random forest classification is developed and applied to representative cases drawn from air pollution control. The model explained 14% of the variance observed in the field data. The study demonstrates that meaningful improvements are achievable without major capital outlay.
Keywords:
bridge structural health monitoringrandom forest classificationenergy managementcognitive radiooptimisation
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