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 …
[HTML][HTML] Novel logic mining incorporating log linear approach
Mining the best logical rule from the data is a challenging task because not all attribute of the
dataset will contribute towards the optimal logical representation. Even if the correct …
dataset will contribute towards the optimal logical representation. Even if the correct …
Supervised learning perspective in logic mining
Creating optimal logic mining is strongly dependent on how the learning data are structured.
Without optimal data structure, intelligence systems integrated into logic mining, such as an …
Without optimal data structure, intelligence systems integrated into logic mining, such as an …
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 …
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 …
[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 …
Machine Learning Methods for Predicting League of Legends Game Outcome
JA Hitar-García, L Morán-Fernández… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
The video game League of Legends has several professional leagues and tournaments that
offer prizes reaching several million dollars, making it one of the most followed games in the …
offer prizes reaching several million dollars, making it one of the most followed games in the …
Amazon employees resources access data extraction via clonal selection algorithm and logic mining approach
Amazon. com Inc. seeks alternative ways to improve manual transactions system of granting
employees resources access in the field of data science. The work constructs a modified …
employees resources access in the field of data science. The work constructs a modified …
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 …