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Artificial neural network

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Definitions Edit

An artificial neural network is

[a] linked network of simple software-based processors, analogous to a biological neural network, that can be trained as an ensemble to respond consistently to a set of numerical input stimuli.[1]
[a] computer architecture modeled after the human brain and designed to solve problems that human brains solve well, such as recognizing patterns and making predictions from past performance. Neural networks are composed of interconnected computer processors that calculate a number of weighted inputs to generate an output.[2]

Overview Edit

"For example, an output might be the approval or rejection of a credit application. This output would be based on several inputs, including the applicant's income, current debt, and credit history. Some of these inputs would count more than others; cumulatively, they would be compared to a threshold value that separates approvals from rejections. Neural networks "learn" to generate better outputs by adjusting the weights and thresholds applied to their inputs."[3]

References Edit

  1. Bringing Health Care Online: The Role of Information Technologies, at 215.
  2. Wiki.GIS.com, GIS Glossary (full-text).
  3. Id.

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