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Published in:

Volume 7 Issue 3
March-2020
eISSN: 2349-5162

Unique Identifier

JETIR2003079

Page Number

494-507

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Title

ANN: A Revolutionary Biological Neuron Inspired Paradigm

ISSN

2349-5162

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"ANN: A Revolutionary Biological Neuron Inspired Paradigm ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 3, page no.494-507, March-2020, Available :http://www.jetir.org/papers/JETIR2003079.pdf

Abstract

There are problem categories that cannot be formulated as an algorithm. Many problems depend on many subtle factors. Without an algorithm a computer cannot predict like humans. Humans have a brain that can “learn”. Computers have some processing units and memory. They allow the computer to perform the most complex numerical calculations in a very short time, but they are not adaptive. Artificial neural networks (ANNs) technology is a group of computer methods for modeling and pattern recognition. The ANNs are a type of mathematical model that simulates the biological nervous system and draws on analogues of adaptive biological neurons. Learning process is a human intelligence. This ability permits us to acquire various skills and expertise in numerous fields with reference to changing environment. Our reactions rather say outputs in different -different conditions are totally based on some previous experiences or inputs. So implementing these learning capabilities in machines and predicting the outputs by them is the central goal of Artificial intelligence. Some expert system can be developed to find application in various fields ranging from medicines, agriculture to computer design or etc. such expert systems or we can say models are computer programs which stimulates the expertise of human expert in solving problems. Artificial neural networks (ANNs) are such expert systems which are of simple processing elements (named ‘neurons’) operating on their local data and communicating with other elements. Basic principle is, each neuron in the network can receive input signals, process them and send an output signal in desired form. So, by proper training and validation processes such generalized ANN model can be developed to predict the performance of various dosage forms.

Key Words

ANN, Neuron, Learning, Artificial Intelligence, Pattern recognition

Cite This Article

"ANN: A Revolutionary Biological Neuron Inspired Paradigm ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 3, page no. pp494-507, March-2020, Available at : http://www.jetir.org/papers/JETIR2003079.pdf

Publication Details

Published Paper ID: JETIR2003079
Registration ID: 229383
Published In: Volume 7 | Issue 3 | Year March-2020
DOI (Digital Object Identifier):
Page No: 494-507
ISSN Number: 2349-5162

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Cite This Article

"ANN: A Revolutionary Biological Neuron Inspired Paradigm ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 3, page no. pp494-507, March-2020, Available at : http://www.jetir.org/papers/JETIR2003079.pdf




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