Improving generalization with active learning
Active learning differs from “learning from examples” in that the learning algorithm assumes
at least some control over what part of the input domain it receives information about. In …
at least some control over what part of the input domain it receives information about. In …
Training connectionist networks with queries and selective sampling
Abstract" Selective sampling" is a form of directed search that can greatly increase the ability
of a connectionist network to generalize accu (cid: 173) rately. Based on information from …
of a connectionist network to generalize accu (cid: 173) rately. Based on information from …
Short term load forecasting using a multilayer neural network with an adaptive learning algorithm
KL Ho, YY Hsu, CC Yang - IEEE Transactions on Power …, 1992 - ieeexplore.ieee.org
A multilayer feedforward neural network is proposed for short-term load forecasting. To
speed up the training process, a learning algorithm for the adaptive training of neural …
speed up the training process, a learning algorithm for the adaptive training of neural …
Artificial neural networks and their applications to power systems—a bibliographical survey
VSS Vankayala, ND Rao - Electric power systems research, 1993 - Elsevier
Artificial neural networks (ANNs), representing computational paradigms based on a
biological metaphor, are rapidly gaining popularity among power system researchers. The …
biological metaphor, are rapidly gaining popularity among power system researchers. The …
Tuning of power system stabilizers using an artificial neural network
YY Hsu, CR Chen - IEEE transactions on energy conversion, 1991 - ieeexplore.ieee.org
A new approach using an artificial neural network is proposed to adapt power system
stabilizer (PSS) parameters in real time. A pair of online measurements ie, generator real …
stabilizer (PSS) parameters in real time. A pair of online measurements ie, generator real …
Power system static security assessment using the Kohonen neural network classifier
D Niebur, AJ Germond - IEEE Transactions on Power Systems, 1992 - ieeexplore.ieee.org
The authors present the application of an artificial neural network, Kohonen's self-organizing
feature map, for the classification of power system states. This classifier maps vectors of an …
feature map, for the classification of power system states. This classifier maps vectors of an …
Artificial neural network approach to network reconfiguration for loss minimization in distribution networks
Network reconfiguration of distribution systems is an operation in configuration management
that determines the switching operations for a minimum loss condition. An artificial neural …
that determines the switching operations for a minimum loss condition. An artificial neural …
[PDF][PDF] Query-based learning applied to partially trained multilayer perceptrons
In many machine learning applications, the source of the training data can be modeled as
an oracle. An oracle has the ability, when presented with an example (query), to give a …
an oracle. An oracle has the ability, when presented with an example (query), to give a …
Design of artificial neural networks for short-term load forecasting. Part 1: Self-organising feature maps for day type identification
YY Hsu, CC Yang - IEE Proceedings C (Generation, Transmission and …, 1991 - IET
A new approach using artificial neural networks (ANNs) is proposed for short-term load
forecasting. To forecast the hourly loads of a day, the hourly load pattern and the peak and …
forecasting. To forecast the hourly loads of a day, the hourly load pattern and the peak and …
[BOOK][B] Electric systems, dynamics, and stability with artificial intelligence applications
JA Momoh, ME El-Hawary - 2018 - taylorfrancis.com
This work seeks to provide a solid foundation to the principles and practices of dynamics
and stability assessment of large-scale power systems, focusing on the use of …
and stability assessment of large-scale power systems, focusing on the use of …