Name
Title | ||
|---|---|---|
Particle swarm optimization based neural-network model for hydro power plant dynamics |
Abstract | ||
|---|---|---|
This paper addresses the modeling of hydro power plant dynamics using neural network approach. The cost function as root mean square error is optimized by particle swarm optimization technique. The identification performance is compared with fuzzy models based on GK clustering algorithm in application to study hydro power plant dynamics. It is found that the response obtained from the NN model is comparable to those determined by fuzzy model with much significance to nature of input-output variables used for modeling. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/CEC.2007.4424815 | IEEE Congress on Evolutionary Computation |
Keywords | Field | DocType |
hydroelectric power,mean square error methods,neural nets,particle swarm optimisation,power engineering computing,power plants,cost function,hydro power plant dynamics,identification performance,neural network model,particle swarm optimization,root mean square error optimisation,Approximation,Fuzzy model,Hydro plant,Identification,Neural network model | Particle swarm optimization,Mathematical optimization,Fuzzy model,Computer science,Fuzzy logic,Mean squared error,Multi-swarm optimization,Artificial intelligence,Cluster analysis,Artificial neural network,Hydroelectricity,Machine learning | Conference |
ISBN | Citations | PageRank |
978-1-4244-1340-9 | 1 | 0.41 |
References | Authors | |
3 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nand Kishor | 1 | 78 | 14.41 |
| Madhusudan Singh | 2 | 85 | 10.86 |
| A. S. Raghuvanshi | 3 | 9 | 2.12 |