Modified election algorithm in hopfield neural network for optimal random k satisfiability representation
Election algorithm (EA) is a novel metaheuristics optimization model motivated by phenomena of the socio-political mechanism of presidential election conducted in many countries. The capability and robustness EA in finding an optimal solution to optimization has been proven by various researchers. I...
Main Authors: | Abubakar Hamza, Sabri Shamsul Rijal Muhammad, Abdu Masanawa Sagir, Yusuf Surajo |
---|---|
Format: | Article |
Language: | English |
Published: |
EDP Sciences
2020-01-01
|
Series: | International Journal for Simulation and Multidisciplinary Design Optimization |
Subjects: | |
Online Access: | https://www.ijsmdo.org/articles/smdo/full_html/2020/01/smdo200010/smdo200010.html |
Similar Items
-
Optimal representation to High Order Random Boolean kSatisability via Election Algorithm as Heuristic Search Approach in Hopeld Neural Networks
by: Hamza Abubakar, et al.
Published: (2021-08-01) -
Election Algorithm for Random <i>k</i> Satisfiability in the Hopfield Neural Network
by: Saratha Sathasivam, et al.
Published: (2020-05-01) -
Novel Hopfield Neural Network Model with Election Algorithm for Random 3 Satisfiability
by: Muna Mohammed Bazuhair, et al.
Published: (2021-07-01) -
Discrete Mutation Hopfield Neural Network in Propositional Satisfiability
by: Mohd Shareduwan Mohd Kasihmuddin, et al.
Published: (2019-11-01) -
Genetic Algorithm for Restricted Maximum k-Satisfiability in the Hopfield Network
by: Mohd Shareduwan Bin Mohd Kasihmuddin, et al.
Published: (2016-12-01)