Modified Neural Net for the Boolean Satisfiability Problem
A modified Hopfield Artificial Neural Network is proposed to solve effectively and efficiently Boolean Satisfiability (SAT) NP-hard problems. The proposed Neural Network is compared against other traditional methods employed in this field, such as Greedy SAT and Genetic Algorithms for SAT. The resul...
Saved in:
Published in | 2015 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE) pp. 64 - 69 |
---|---|
Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.11.2015
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | A modified Hopfield Artificial Neural Network is proposed to solve effectively and efficiently Boolean Satisfiability (SAT) NP-hard problems. The proposed Neural Network is compared against other traditional methods employed in this field, such as Greedy SAT and Genetic Algorithms for SAT. The results show that the proposed network represents a good alternative given their output quality and response time speed. |
---|---|
ISBN: | 1467383287 9781467383288 |
DOI: | 10.1109/ICMEAE.2015.46 |