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Automated Generation of Interorganizational Disaster Response Networks through Information Extraction
When a disaster occurs, maintaining and restoring community lifelines subsequently require collective efforts from various stakeholders.
Automated Abstraction of Operation Processes from Unstructured Text for Simulation Modeling
Overall, this research enhances the state-of-the-art simulation modeling through achieving automated abstraction of operation processes, which largely reduces modelers' interpretation load and ensures the reliability of the abstracted operation processes.
Enhanced Input Modeling for Construction Simulation using Bayesian Deep Neural Networks
This paper aims to propose a novel deep learning-integrated framework for deriving reliable simulation input models through incorporating multi-source information.
Complexity Analysis Approach for Prefabricated Construction Products Using Uncertain Data Clustering
This paper proposes an uncertain data clustering approach to quantitatively analyze the complexity of prefabricated construction components through the integration of quality performance-based measures with associated engineering design information.
