Zobrazeno 1 - 10
of 2 348
pro vyhledávání: '"Hopfield Neural Network"'
Autor:
Nur 'Afifah Rusdi, Nur Ezlin Zamri, Mohd Shareduwan Mohd Kasihmuddin, Nurul Atiqah Romli, Gaeithry Manoharam, Suad Abdeen, Mohd. Asyraf Mansor
Publikováno v:
AIMS Mathematics, Vol 9, Iss 11, Pp 29820-29882 (2024)
The current systematic logical rules in the Discrete Hopfield Neural Network encounter significant challenges, including repetitive final neuron states that lead to the issue of overfitting. Furthermore, the systematic logical rules neglect the impac
Externí odkaz:
https://doaj.org/article/bd75417beea34205b685206cf7e10072
Publikováno v:
AIMS Mathematics, Vol 9, Iss 10, Pp 28100-28129 (2024)
The discrete Hopfield neural network 3-satisfiability (DHNN-3SAT) model represents an innovative application of deep learning techniques to the Boolean SAT problem. Existing research indicated that the DHNN-3SAT model demonstrated significant advanta
Externí odkaz:
https://doaj.org/article/8e88b874c68b4f8e8369b969ba444734
Autor:
Nurul Atiqah Romli, Nur Fariha Syaqina Zulkepli, Mohd Shareduwan Mohd Kasihmuddin, Nur Ezlin Zamri, Nur 'Afifah Rusdi, Gaeithry Manoharam, Mohd. Asyraf Mansor, Siti Zulaikha Mohd Jamaludin, Amierah Abdul Malik
Publikováno v:
AIMS Mathematics, Vol 9, Iss 8, Pp 22321-22365 (2024)
Evaluating behavioral patterns through logic mining within a given dataset has become a primary focus in current research. Unfortunately, there are several weaknesses in the research regarding the logic mining models, including an uncertainty of the
Externí odkaz:
https://doaj.org/article/bb96c96566734319b76d8d1981cc994f
Autor:
Gaeithry Manoharam, Azleena Mohd Kassim, Suad Abdeen, Mohd Shareduwan Mohd Kasihmuddin, Nur 'Afifah Rusdi, Nurul Atiqah Romli, Nur Ezlin Zamri, Mohd. Asyraf Mansor
Publikováno v:
AIMS Mathematics, Vol 9, Iss 5, Pp 12090-12127 (2024)
Currently, the discrete Hopfield neural network deals with challenges related to searching space and limited memory capacity. To address this issue, we propose integrating logical rules into the neural network to regulate neuron connections. This app
Externí odkaz:
https://doaj.org/article/05c48455aa084713811f3a30d4fa5ed5
Publikováno v:
AIMS Mathematics, Vol 9, Iss 2, Pp 3911-3956 (2024)
The current development of logic satisfiability in discrete Hopfield neural networks (DHNN)has been segregated into systematic logic and non-systematic logic. Most of the research tends to improve non-systematic logical rules to various extents, such
Externí odkaz:
https://doaj.org/article/b7c29c5f5d3a4a18adb9724fe7a8ebc2
Publikováno v:
AIMS Mathematics, Vol 9, Iss 2, Pp 3150-3173 (2024)
Since the beginning of the Covid-19 infections in December 2019, the virus has emerged as the most lethally contagious in world history. In this study, the Hopfield neural network and logic mining technique merged to extract data from a model to prov
Externí odkaz:
https://doaj.org/article/ac14728dbef64d25b026da221d08b6be
Publikováno v:
Frontiers in Computational Neuroscience, Vol 18 (2024)
A good intelligent learning model is the key to complete recognition of scene information and accurate recognition of specific targets in intelligent unmanned system. This study proposes a new associative memory model based on the semi-tensor product
Externí odkaz:
https://doaj.org/article/31be0b1243fb444e9ad05fa0da4e5a55
Autor:
Mohammed D. Kassim
Publikováno v:
AIMS Mathematics, Vol 8, Iss 11, Pp 26343-26356 (2023)
Of concern is the Hopfield neural network system comprising discrete as well as distributed delays in the form of a convolution. For a desired convergence rate of the solution to the equilibrium state, we establish sufficient conditions on the delay
Externí odkaz:
https://doaj.org/article/2d27a74b5a3f4f3b87f75c992f899689
Autor:
Muhammad Aqmar Fiqhi Roslan, Nur Ezlin Zamri, Mohd. Asyraf Mansor, Mohd Shareduwan Mohd Kasihmuddin
Publikováno v:
AIMS Mathematics, Vol 8, Iss 9, Pp 22447-22482 (2023)
Discrete Hopfield Neural Network is widely used in solving various optimization problems and logic mining. Boolean algebras are used to govern the Discrete Hopfield Neural Network to produce final neuron states that possess a global minimum energy so
Externí odkaz:
https://doaj.org/article/5354213442994eaaa10a07ca3b48964a
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
With the advancement of smart grid construction, higher requirements have been put forward for energy meter data, which need to realize real-time, accurate, efficient, safe, and economical data transmission. In this paper, an intelligent collection o
Externí odkaz:
https://doaj.org/article/963c26b67123456d94e23d5a445fbf34