Human-inspired optimization algorithms: Theoretical foundations, algorithms, open-research issues and application for multi-level thresholding
Humans take immense pride in their ability to be unpredictably intelligent and despite huge
advances in science over the past century; our understanding about human brain is still far …
advances in science over the past century; our understanding about human brain is still far …
Weighted random k satisfiability for k= 1, 2 (r2SAT) in discrete Hopfield neural network
Current studies on non-systematic satisfiability in Discrete Hopfield Neural Network are able
to avoid production of repetitive final neuron states which improves the quality of global …
to avoid production of repetitive final neuron states which improves the quality of global …
YRAN2SAT: A novel flexible random satisfiability logical rule in discrete hopfield neural network
The current development of the satisfiability logical representation in Discrete Hopfield
Neural Network has two prominent perspectives which are systematic and non-systematic …
Neural Network has two prominent perspectives which are systematic and non-systematic …
A modified reverse-based analysis logic mining model with Weighted Random 2 Satisfiability logic in Discrete Hopfield Neural Network and multi-objective training of …
Over the years, the study on logic mining approach has increased exponentially. However,
most logic mining models disregarded any efforts in expanding the search space which led …
most logic mining models disregarded any efforts in expanding the search space which led …
PRO2SAT: Systematic probabilistic satisfiability logic in discrete hopfield neural network
Satisfiability is prominent in the field of computer science and mathematics because SAT
provides an alternative to represent the knowledge of any datasets. Fueled by this nature …
provides an alternative to represent the knowledge of any datasets. Fueled by this nature …
Non-systematic weighted satisfiability in discrete hopfield neural network using binary artificial bee colony optimization
SS Muhammad Sidik, NE Zamri… - Mathematics, 2022 - mdpi.com
Recently, new variants of non-systematic satisfiability logic were proposed to govern
Discrete Hopfield Neural Network. This new variant of satisfiability logical rule will provide …
Discrete Hopfield Neural Network. This new variant of satisfiability logical rule will provide …
Multi-discrete genetic algorithm in hopfield neural network with weighted random k satisfiability
Abstract The existing Discrete Hopfield Neural Network with systematic Satisfiability models
produced repetition of final neuron states which promotes to overfitting global minima …
produced repetition of final neuron states which promotes to overfitting global minima …
Random satisfiability: A higher-order logical approach in discrete Hopfield Neural Network
A conventional systematic satisfiability logic suffers from a nonflexible logical structure that
leads to a lack of interpretation. To resolve this problem, the advantage of introducing …
leads to a lack of interpretation. To resolve this problem, the advantage of introducing …
[HTML][HTML] Multi-unit Discrete Hopfield Neural Network for higher order supervised learning through logic mining: Optimal performance design and attribute selection
In the perspective of logic mining, the attribute selection, and the objective function of the
best logic is the two main factors that identifies the effectiveness of our proposed logic …
best logic is the two main factors that identifies the effectiveness of our proposed logic …
Major 2 satisfiability logic in discrete Hopfield neural network
Existing satisfiability (SAT) is composed of a systematic logical structure with definite literals
in a set of clauses. The key problem of the existing SAT is the lack of interpretability of a …
in a set of clauses. The key problem of the existing SAT is the lack of interpretability of a …