The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Kertas kerja ini membentangkan algoritma pembelajaran yang fleksibel untuk rangkaian saraf binari yang boleh merealisasikan fungsi Boolean yang dikehendaki. Algoritma menentukan parameter lapisan tersembunyi menggunakan algoritma genetik. Ia boleh mengurangkan bilangan neuron tersembunyi dan boleh menyekat penyebaran parameter. Kelebihan ini disahkan oleh eksperimen berangka asas.
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Salinan
Masanori SHIMADA, Toshimichi SAITO, "A GA-Based Learning Algorithm for Binary Neural Networks" in IEICE TRANSACTIONS on Fundamentals,
vol. E85-A, no. 11, pp. 2544-2546, November 2002, doi: .
Abstract: This paper presents a flexible learning algorithm for the binary neural network that can realize a desired Boolean function. The algorithm determines hidden layer parameters using a genetic algorithm. It can reduce the number of hidden neurons and can suppress parameters dispersion. These advantages are verified by basic numerical experiments.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e85-a_11_2544/_p
Salinan
@ARTICLE{e85-a_11_2544,
author={Masanori SHIMADA, Toshimichi SAITO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A GA-Based Learning Algorithm for Binary Neural Networks},
year={2002},
volume={E85-A},
number={11},
pages={2544-2546},
abstract={This paper presents a flexible learning algorithm for the binary neural network that can realize a desired Boolean function. The algorithm determines hidden layer parameters using a genetic algorithm. It can reduce the number of hidden neurons and can suppress parameters dispersion. These advantages are verified by basic numerical experiments.},
keywords={},
doi={},
ISSN={},
month={November},}
Salinan
TY - JOUR
TI - A GA-Based Learning Algorithm for Binary Neural Networks
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2544
EP - 2546
AU - Masanori SHIMADA
AU - Toshimichi SAITO
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E85-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 2002
AB - This paper presents a flexible learning algorithm for the binary neural network that can realize a desired Boolean function. The algorithm determines hidden layer parameters using a genetic algorithm. It can reduce the number of hidden neurons and can suppress parameters dispersion. These advantages are verified by basic numerical experiments.
ER -