How do Artificial Neural Networks Work

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Published: Sep 2, 2024
DOI: https://doi.org/10.29070/ttrkmm98
Keywords:
Artificial Neural Networks, computer models, human brain, neurons, layers, information, connections, weights, learning process, input data, predictions, classifications, training, output, error, optimization methods, image identification, natural language processing, decision-making, artificial intelligence

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Authors

Aryan Rose

Class 12, Welham Boys School

Abstract

Artificial Neural Networks (ANNs) are computer models inspired by the structure and operation ofthe human brain. They comprise of linked nodes, called neurons, grouped in layers. Information passesacross these neurons, and each connection between neurons is connected with a weight denoting itssignificance. The network's learning process includes altering these weights depending on input data toincrease its capacity to generate correct predictions or classifications. During training, the networkcompares its output to the intended output, computes the error, and then applies optimization methods toreduce this error. Once trained, ANNs may be used for numerous tasks, including as image identification,natural language processing, and decision-making, making them a formidable tool in the area of artificialintelligence.

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Article Details

Issue

Vol. 20 No. 1 (2023): Journal of Advances in Science and Technology (JAST)

Section

Articles

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