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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
A System-Of-Systems Framework For Assessment Of Resilience In Complex Construction Projects, Jin Zhu
A System-Of-Systems Framework For Assessment Of Resilience In Complex Construction Projects, Jin Zhu
FIU Electronic Theses and Dissertations
Uncertainty is a major reason of low efficiency in construction projects. Traditional approaches in dealing with uncertainty in projects focus on risk identification, mitigation, and transfer. These risk-based approaches may protect projects from identified risks. However, they cannot ensure the success of projects in environments with deep uncertainty. Hence, there is a need for a paradigm shift from risk-based to resilience-based approaches. A resilience-based approach focuses on enhancing project resilience as a capability to cope with known and unknown uncertainty. The objective of this research is to fill the knowledge gap and create the theory of resilience in the context …
A Recommendation System For Meta-Modeling: A Meta-Learning Based Approach, Can Cui, Mengqi Hu, Jeffery D. Weir, Teresa Wu
A Recommendation System For Meta-Modeling: A Meta-Learning Based Approach, Can Cui, Mengqi Hu, Jeffery D. Weir, Teresa Wu
Faculty Publications
Various meta-modeling techniques have been developed to replace computationally expensive simulation models. The performance of these meta-modeling techniques on different models is varied which makes existing model selection/recommendation approaches (e.g., trial-and-error, ensemble) problematic. To address these research gaps, we propose a general meta-modeling recommendation system using meta-learning which can automate the meta-modeling recommendation process by intelligently adapting the learning bias to problem characterizations. The proposed intelligent recommendation system includes four modules: (1) problem module, (2) meta-feature module which includes a comprehensive set of meta-features to characterize the geometrical properties of problems, (3) meta-learner module which compares the performance of instance-based …