Learning Logic Programming in Radial Basis Function Network via Genetic Algorithm

Higher Order Logic Programming in Radial Basis Function Neural Network

Intelligent systems are yielded from integration of a logic programming and connectionist systems. Radial basis function neural network is a commonly-used type of feedforward networks. In this paper, we proposed a method for connectionist model generation using Radial Basis Function neural network to encode higher order logic programming. We encode each clause from the clauses of a logic progra...

Radial Basis Function Neural Network With Dynamic Optimal Learning Rate & Genetic Algorithm

This paper presents a training method for radial basis function neural network (RBFNN) based on GA and dynamic optimal learning rate. Genetic algorithm (GA) is applied to search for the optimal centers from input space of the RBF. Dynamic optimal learning rate approach is also appended to the genetic algorithms’ searching procession to obtain a set of weighting factors so that the network actua...

Training Radial Basis Function Neural Network using Stochastic Fractal Search Algorithm to Classify Sonar Dataset

Radial Basis Function Neural Networks (RBF NNs) are one of the most applicable NNs in the classification of real targets. Despite the use of recursive methods and gradient descent for training RBF NNs, classification improper accuracy, failing to local minimum and low-convergence speed are defects of this type of network. In order to overcome these defects, heuristic and meta-heuristic algorith...

Neural Logic Network Learning using Genetic Programming

Neural Logic Network or Neulonet is a hybrid of neural network expert systems. Its strength lies in its ability to learn and to represent human logic in decision making using component net rules. The technique originally employed in neulonet learning is backpropagation. However, the resulting weight adjustments will lead to a loss in the logic of the net rules. A new technique is now developed ...

A Grammatical Genetic Programming Representation for Radial Basis Function Networks