Systematic Boolean Satisfiability Programming in Radial Basis Function Neural Network

Systematic Boolean Satisfiability Programming in Radial Basis Function Neural Network

Radial Basis Function Neural Network (RBFNN) is a class of Artificial Neural Network (ANN) that contains hidden layer processing units (neurons) with nonlinear, radially symmetric activation functions. Consequently, RBFNN has extensively suffered from significant computational error and difficulties...

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Bibliographic Details
Main Authors: Mohd. Asyraf Mansor, Siti Zulaikha Mohd Jamaludin, Mohd Shareduwan Mohd Kasihmuddin, Shehab Abdulhabib Alzaeemi, Md Faisal Md Basir, Saratha Sathasivam
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Processes
Subjects:
radial basis function neural network
hopfield neural network
satisfiability
optimization
logic programming
Online Access:https://www.mdpi.com/2227-9717/8/2/214

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https://www.mdpi.com/2227-9717/8/2/214

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