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- <p>Pattern recognition systems<br />Machine learning<br />Swarm intelligence<br />Time-series analysis</p> (1)
- <p>Smart power grids -- Mathematical models<br />Electric power failures -- Prevention<br />Intelligent control systems</p> (1)
- Adaptive Resonance Theory (1)
- Clustering (1)
- Particle Swarm Optimization (1)
Articles 1 - 2 of 2
Full-Text Articles in Computer Engineering
Dependability Analysis And Recovery Support For Smart Grids, Isam Abdulmunem Alobaidi
Dependability Analysis And Recovery Support For Smart Grids, Isam Abdulmunem Alobaidi
Masters Theses
"The increasing scale and complexity of power grids exacerbate concerns about failure propagation. A single contingency, such as outage of a transmission line due to overload or weather-related damage, can cause cascading failures that manifest as blackouts. One objective of smart grids is to reduce the likelihood of cascading failure through the use of power electronics devices that can prevent, isolate, and mitigate the effects of faults. Given that these devices are themselves prone to failure, we seek to quantify the effects of their use on dependability attributes of smart grid. This thesis articulates analytical methods for analyzing two dependability …
Fuzzy Adaptive Resonance Theory: Applications And Extensions, Clayton Parker Smith
Fuzzy Adaptive Resonance Theory: Applications And Extensions, Clayton Parker Smith
Masters Theses
"Adaptive Resonance Theory, ART, is a powerful clustering tool for learning arbitrary patterns in a self-organizing manner. In this research, two papers are presented that examine the extensibility and applications of ART. The first paper examines a means to boost ART performance by assigning each cluster a vigilance value, instead of a single value for the whole ART module. A Particle Swarm Optimization technique is used to search for desirable vigilance values. In the second paper, it is shown how ART, and clustering in general, can be a useful tool in preprocessing time series data. Clustering quantization attempts to meaningfully …