A solution method using neural networks for the generator commitment problem
β Scribed by Hiroshi Sasaki; Yuuji Fujii; Masahiro Watanabe; Junji Kubokawa; Naoto Yorino
- Book ID
- 112081877
- Publisher
- John Wiley and Sons
- Year
- 1992
- Tongue
- English
- Weight
- 535 KB
- Volume
- 112
- Category
- Article
- ISSN
- 0424-7760
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Generally, to find the optimal release time for a software product, the parametric estimation values of the mean value function, which characterizes the software reliability growth model, are determined from the fault detection time data observed during the testing phase, and an analytical method is
The general approximation problem of interest to the area of feedforward neural net works is stated. Solutions for som e special cases are given. which include an upper bound on the number ofnodes in hidden layerts ) and the weights for that confi guration. Analytical solutions to the generalfeedfo
This paper introduces an alternative method artificial neural networks (ANN) used to obtain numerical solutions of mathematical models of dynamic systems, represented by ordinary differential equations (ODEs) and partial differential equations (PDEs). The proposed trial solution of differential equa