An Overview on the Artificial Neural Network

Authors

  • Jitender Kumar Assistant Professor, Department of Computer Science and Engineering, Vivekananda Global, University, Jaipur, India Author

Keywords:

Artificial Neural Network, Algorithm, Deep learning, MATLAB.

Abstract

Deep learning is the cutting edge of  artificial intelligence, which is already at the forefront (AI)  (AI). Machine learning, on the other hand, is meant to  teach computers how to interpret and learn from data. Deep  learning enables a computer to continually educate itself to  examine data, learn from it, and enhance its capabilities.  This article gives a quick description of the Artificial  Neural Network forecasting method (ANN) (ANN). It is  used to boost the model's forecast accuracy while lowering  the model's dependency on test data or current value. The  fundamental developments in technology that have been  applied in MATLAB are described, as well as distinct  ANN discrete sets. The goal of the preparation is to keep  the input equations' mean square errors to a minimal. The  ANN model may be used to forecast yield boundaries,  which assists in the best estimation of machining borders  for the purpose of measuring improving streamlining  machining boundaries. 

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Published

2020-05-05

Issue

Vol. 8 No. 3 (2020): International Journal of Innovative Research in Computer Science and Technology (May) 2020

Section

Articles

How to Cite

An Overview on the Artificial Neural Network . (2020). International Journal of Innovative Research in Computer Science & Technology, 8(3), 274–278. Retrieved from https://acspublisher.com/journals/index.php/ijircst/article/view/13322