Radial basis function neural network for 2 satisfiability programming

Radial basis function neural network for 2 satisfiability programming

Radial Basis Function Neural Network (RBFNN) is very prominent in data processing. However, improving this technique is vital for the NN training process. This paper presents an integrated 2 Satisfiability in radial basis function neural network (RBFNN-2SAT). There are two different types of trainin...

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Hauptverfasser: Alzaeemi, Shehab (VerfasserIn), Mansor, Mohd. Asyraf (VerfasserIn), Kasihmuddin, Mohd Shareduwan Mohd (VerfasserIn), Sathasivam, Saratha (VerfasserIn), Mamat, Mustafa (VerfasserIn)
Weitere Verfasser: This research is funded by School of Mathematical Sciences, Universiti Sains Malaysia, Grant number: 1001.PMATHS.AUPS001 (MitwirkendeR)
Format: EJournal Article
Veröffentlicht: Institute of Advanced Engineering and Science, 2020-04-01.
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info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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