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Articles 1 - 3 of 3
Full-Text Articles in Engineering
Behaviorally Enriched Learning Mechanism For Road Network Emergency Restoration After Disasters, Maryam Babaee
Behaviorally Enriched Learning Mechanism For Road Network Emergency Restoration After Disasters, Maryam Babaee
FIU Electronic Theses and Dissertations
Timely restoration of road networks plays a critical role in the response operations after disasters and helps communities turn back to their normal operations soon. Scarcity of restoration resources, uncertainty of recovery times, and behavioral variations of travelers are the major factors that highly complicate road network restoration operations. Here, these challenges are addressed by developing a Behaviorally-enriched Reinforcement Learning Mechanism (BRLM). Considering gradual adaptation of travelers, the mechanism optimizes scheduling and resource allocation decisions in the restoration process to make the highest acceleration in the post-disaster traffic movement. The performance of BRLM is tested on the road network of …
Digital Twin-Based Cooperative Control Techniques For Secure And Intelligent Operation Of Distributed Microgrids, Ahmed Aly Saad Ahmed
Digital Twin-Based Cooperative Control Techniques For Secure And Intelligent Operation Of Distributed Microgrids, Ahmed Aly Saad Ahmed
FIU Electronic Theses and Dissertations
Networked microgrids play a key role in constructing future active distribution networks for providing the power system with resiliency and reliability against catastrophic physical and cyber incidents. Motivated by the increasing penetration of renewable resources and energy storage systems in the distribution grids, utility companies are encouraged to unleash the capabilities of the distributed microgrid to work as virtual power plants that can support the power systems. The microgrids nature is transforming the grid and their control systems from centralized architecture into distributed architectures. The distributed networked microgrids introduced many benefits to the future smart grids, it created many challenges …
A Mathematical Framework On Machine Learning: Theory And Application, Bin Shi
A Mathematical Framework On Machine Learning: Theory And Application, Bin Shi
FIU Electronic Theses and Dissertations
The dissertation addresses the research topics of machine learning outlined below. We developed the theory about traditional first-order algorithms from convex opti- mization and provide new insights in nonconvex objective functions from machine learning. Based on the theory analysis, we designed and developed new algorithms to overcome the difficulty of nonconvex objective and to accelerate the speed to obtain the desired result. In this thesis, we answer the two questions: (1) How to design a step size for gradient descent with random initialization? (2) Can we accelerate the current convex optimization algorithms and improve them into nonconvex objective? For application, …