[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 …
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 …
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 …
[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 …
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 …
Election Algorithm for Random k Satisfiability in the Hopfield Neural Network
Election Algorithm (EA) is a novel variant of the socio-political metaheuristic algorithm,
inspired by the presidential election model conducted globally. In this research, we will …
inspired by the presidential election model conducted globally. In this research, we will …
GRAN3SAT: Creating flexible higher-order logic satisfiability in the discrete hopfield neural network
One of the main problems in representing information in the form of nonsystematic logic is
the lack of flexibility, which leads to potential overfitting. Although nonsystematic logic …
the lack of flexibility, which leads to potential overfitting. Although nonsystematic logic …
Analysis and optimization of network properties for bionic topology hopfield neural network using gaussian-distributed small-world rewiring method
J Sun, S Sathasivam, MKBM Ali - IEEE Access, 2022 - ieeexplore.ieee.org
The fully connected topology, which coordinates the connection of each neuron with all
other neurons, remains the most commonly used structure in Hopfield-type neural networks …
other neurons, remains the most commonly used structure in Hopfield-type neural networks …
Discrete mutation Hopfield neural network in propositional satisfiability
The dynamic behaviours of an artificial neural network (ANN) system are strongly dependent
on its network structure. Thus, the output of ANNs has long suffered from a lack of …
on its network structure. Thus, the output of ANNs has long suffered from a lack of …