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Machine Learning Based Fast Power Integrity Classifier
In this paper, we proposed a new machine learning based fast power integ...
11/08/2017 ∙ by HuaChun Zhang, et al. ∙
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Power Grid State Estimation under General Cyber-Physical Attacks
Effective defense against cyber-physical attacks in power grid requires ...
09/04/2020 ∙ by Yudi Huang, et al. ∙
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Auction-based approximate algorithm for Grid system scheduling under resource provider strategies
In this paper a new mathematical model is proposed for task scheduling a...
03/12/2018 ∙ by Arash Raeisi Gahrouei, et al. ∙
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Detecting Zero-day Controller Hijacking Attacks on the Power-Grid with Enhanced Deep Learning
Attacks against the control processor of a power-grid system, especially...
06/18/2018 ∙ by Zecheng He, et al. ∙
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Depth First Always On Routing Trace Algorithm
In this paper, we discussed current limitation in the electronic-design-...
11/11/2017 ∙ by Anthony Kim, et al. ∙
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Customized Routing Optimization Based on Gradient Boost Regressor Model
In this paper, we discussed limitation of current electronic-design-auto...
10/28/2017 ∙ by Chen Zheng, et al. ∙
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A Friendly Smoothed Analysis of the Simplex Method
Explaining the excellent practical performance of the simplex method for...
11/15/2017 ∙ by Daniel Dadush, et al. ∙
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LP-Based Power Grid Enhancement Methodology
11/20/2017 ∙ by Tapio Bohn, et al. ∙
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In this paper, we explored the opportunity to enhance power grid robustness after routing stage, and propose a linear programming based algorithm that maximizes the improvement of power grid strengthening with given available routing resource. We further discussed some techniques to leverage tradeoffs between runtime and optimality of the solutions. Experimental results show substantial power integrity improvement with "zero cost".
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