Biological Inspiration—Theoretical Framework Mitosis Artificial Neural Networks Unsupervised Algorithm

Lácides Pinto Mindiola, Gelvis Melo Freile, Carlos Socarras Bertiz

Universidad de La Guajira, Riohacha, Colombia.

DOI: 10.4236/ijcns.2015.89036                

Abstract

The modified approach to conventional Artificial Neural Networks (ANN) described in this paper represents an essential departure from the conventional techniques of structural analysis. It has four main distinguishing features: 1) it introduces a new simulation algorithm based on the biology; 2) it performs relatively simple arithmetic as massively parallel, during analysis of a structure; 3) it shows that it is possible to use the application of the modified approach to conventional ANN to solve problems of any complexity in the field of structural analysis; 4) the Neural Topologies for Structural Analysis (NTSA) system are recurrent networks and its outputs are connected to its inputs [1] and [2]. In NTSA system the DNA of the neuron mother and daughters would be defined by: 1) the same entry, from the corresponding neuron in the previous layer; 2) the same trend vector; 3) the same transfer function (purelin). The mother’s neuron and her daughter’s neuron differ only in the connection weight and its output signal.

Keywords

Mitosis, Artificial Neuron, Node, Structural Analysis, Neural Networks, Output, Layer, Simulation

Conflicts of Interest

The authors declare no conflicts of interest.

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