Data Processing on Large Interdependent Networks: An Application for Infrastructure Preparedness, and Restoration


This paper presents a method for validating and transforming data for use in interdependent infrastructure network analysis. Critical infrastructure are interdependent on each other for delivery of services and execution of restoration activities.  These interdependencies make infrastructure systems vulnerable to extreme events and highlights the needs for preparedness and response plans.  Optimization models have been used to create effective plans using interdependent infrastructure networks.  These models require accurate input data.  However, many data sources have inconsistencies or errors which inhibit the ability to use such optimization models.   This work identifies common errors in input network data and provides a method for processing and correcting these errors.  We demonstrate the effectiveness of this method on data representing the transportation network in Juan Diaz town, in Panama.


Keywords: Data processing, network, infrastructure, interdependence.

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