Power system event identification based on deep neural network with information loading
Online power system event identification and classification are crucial to enhancing the
reliability of transmission systems. In this paper, we develop a deep neural network (DNN) …
reliability of transmission systems. In this paper, we develop a deep neural network (DNN) …
Improving supervised phase identification through the theory of information losses
This paper considers the problem of Phase Identification in power distribution systems. In
particular, it focuses on improving supervised learning accuracies by focusing on exploiting …
particular, it focuses on improving supervised learning accuracies by focusing on exploiting …
Effects of nonlinearity and network architecture on the performance of supervised neural networks
The nonlinearity of activation functions used in deep learning models is crucial for the
success of predictive models. Several simple nonlinear functions, including Rectified Linear …
success of predictive models. Several simple nonlinear functions, including Rectified Linear …
Adversarial attacks on deep neural network-based power system event classification models
Online event classification is essential to strengthening the reliability of the power
transmission system. Recently, deep learning based methods have achieved great success …
transmission system. Recently, deep learning based methods have achieved great success …
On the maximum mutual information capacity of neural architectures
We derive the closed-form expression of the maximum mutual information-the maximum
value of $ I (X; Z) $ obtainable via training-for a broad family of neural network architectures …
value of $ I (X; Z) $ obtainable via training-for a broad family of neural network architectures …
Analyzing data selection techniques with tools from the theory of information losses
In this paper, we present and illustrate some new tools for rigorously analyzing training data
selection methods. These tools focus on the information theoretic losses that occur when …
selection methods. These tools focus on the information theoretic losses that occur when …
[BUKU][B] Intelligent Control and Data-Driven Algorithms for Critical Infrastructure Systems
J Shi - 2021 - search.proquest.com
The rapid development of computing devices and artificial intelligence (AI) in recent
decades have dramatically reshaped the ecosystem of critical infrastructure systems …
decades have dramatically reshaped the ecosystem of critical infrastructure systems …
[BUKU][B] Information Losses in Neural Classifiers With Applications to Training Data Selection Strategies and Cyber Physical Systems
BJ Foggo - 2019 - search.proquest.com
This dissertation considers the subject of information losses arising from finite datasets used
in the training of neural classifiers. It proves a relationship between such losses and the …
in the training of neural classifiers. It proves a relationship between such losses and the …