TITLE:
Biological Inspiration—Theoretical Framework Mitosis Artificial Neural Networks Unsupervised Algorithm
AUTHORS:
Lácides Pinto Mindiola, Gelvis Melo Freile, Carlos Socarras Bertiz
KEYWORDS:
Mitosis, Artificial Neuron, Node, Structural Analysis, Neural Networks, Output, Layer, Simulation
JOURNAL NAME:
International Journal of Communications, Network and System Sciences,
Vol.8 No.9,
September
30,
2015
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.