DOI: 10.5176/2251-2217_SEA12.26

Authors: Yu-Cheng Wang, Toly Chen

Abstract: Artificial neural networks (ANN) have been shown to
perform well in classification and prediction problems. The
technology of ANN can be used to complete information
processing of the networks through the interaction of neural cells.
The mappings of the stimuli effects and the input and output
estimates are obtained through combinations of nonlinear
functions. This offers the advantages of self-learning, selforganization,
self-adaptation, and fault tolerance. ANN also has
possible applications for predicting the gender of a crab.
Additionally, ANN technology allows multiple variables in both
the input and output layers.
In order to find the optimal prediction scheme, this paper uses
the Back-Propagation Network model with a single hidden layer
to focus on the medical conditions of determining the gender of a
crab. This is then compared with the Regression Analysis
Method. We found that the results of the Back-Propagation
Network are more accurate.
Keywords: Gender of Crab; Regression Analysis; Back-
Propagation Network;

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