Analysis of Artificial Neural Networks

Running head: ANALYSIS OF ARTIFICIAL NEURAL NETWORKS
ANALYSIS OF ARTIFICIAL NEURAL NETWORKS
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ANALYSIS OF ARTIFICIAL NEURAL NETWORKS1
Table of Contents
Introduction................................................................................................................................2
Explain the characteristics of artificial neural networks............................................................2
How and Why ANN is used.......................................................................................................3
Value proposition associated with neural networks for solving business problems..................4
Comparison in between neural networks and logistic regression..............................................4
Conclusion..................................................................................................................................5
References:.................................................................................................................................6

ANALYSIS OF ARTIFICIAL NEURAL NETWORKS2
Introduction
Artificial Neural Network is basically based on simulation of the working process of human
brain. This technology have been gaining higher acceptance and hence wise it can be stated
that proper research and development have been carried out in this field (Van Gerven &
Bohte, 2017). This report discusses about the characteristics of Artificial Neural Network.
This report also provides a vivid understanding of the application of the neural network and
hence wise solve the business problems that are present in the operating process. Comparison
in between the neural network as well as logical regression is also made in the report.
Explain the characteristics of artificial neural networks
Some of the characteristics of artificial neural network are the followings (Chen et al., 2017):
 It is a mathematical model which is implemented considering principles of neural
system.
 It contains various processing elements which are interconnected and these processing
elements are referred to as neurons which is are responsible for executing intelligent
operations of applications for which it is designed
 Information that is stored in the neurons are nothing but the weighted linkage of
neurons
 The input signals associated with the processing elements arrive through various
connections and connecting weights of the network as well
 It is capable of learning, recalling and generalizing data from provided data set and
for this it assigns and adjust weights