Hopfield neural networks in large-scale linear optimization problems
โ Scribed by Marta I. Velazco Fontova; Aurelio R.L. Oliveira; Christiano Lyra
- Book ID
- 113440106
- Publisher
- Elsevier Science
- Year
- 2012
- Tongue
- English
- Weight
- 178 KB
- Volume
- 218
- Category
- Article
- ISSN
- 0096-3003
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๐ SIMILAR VOLUMES
The Hop.fteld neural networks are ~:~tended to handle inequality constraints where linear combinations of variables are lower-or upper-bounded. Then b)' eigenvahw analysis, the effects q/'the inequality constraints are analyzed and the lbllowing results are obtained" (a) f a combinatorial solution o
## Abstract When solving optimization problems on Hopfield neural networks, good solutions are not obtained due to convergence to local minima of the energy function. The Boltzmann machine can escape from local minima because of its stochastic behavior, but the computation time is very long to reac