Computational intelligence PC tools
Computational intelligence PC tools
Journal of Global Optimization
Recent approaches to global optimization problems through Particle Swarm Optimization
Natural Computing: an international journal
Parallel evolutionary training algorithms for “hardware-friendly“ neural networks
Natural Computing: an international journal
A neural root finder of polynomials based on root moments
Neural Computation
Determining the number of real roots of polynomials through neural networks
Computers & Mathematics with Applications
IEEE Transactions on Neural Networks
Applicability of feed-forward and recurrent neural networks to Boolean function complexity modeling
Expert Systems with Applications: An International Journal
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In this paper, we propose two approaches to approximate high order multivariate polynomials and to estimate the number of roots of high order univariate polynomials. We employ high order neural networks such as Ridge Polynomial Networks and Pi -- Sigma Networks, respectively. To train the networks efficiently and effectively, we recommend the application of stochastic global optimization techniques. Finally, we propose a two step neural network based technique, to estimate the number of roots of a high order univariate polynomial.