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• W2494038574 abstract "Neural network development and applications have increased in several areas of science to the extent that neural networks are the most actively used of the available artificial intelligence tools. This chapter is confined primarily to introducing fishery scientists to neural network methodology and applications in biological classification. However, this is preceded by a very short introduction to neural networks and some of its terminology. For the purposes, neural networks are defined as models of real-world systems which are built by training a set of parameters. These parameters, which are called weights, describe a model that forms a mapping from a set of given values known as inputs to an associated set of values known as outputs. The process of finding the weights for the correct values is called training, and it is usually carried out by passing sets of input–output pairs through the model and adjusting the weights in order to minimize the error between the answer the network provides and the desired output. Once the weights have been set by suitable training, the model is able to produce answers for input values which are not included in the training data. The models do not refer to the training data after they have been trained, and in some sense they are a functional summary of the training data." @default.
• W2494038574 created "2016-08-23" @default.
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• W2494038574 date "2005-01-01" @default.
• W2494038574 modified "2023-09-27" @default.
• W2494038574 title "Neural Networks Used in Classification with Emphasis on Biological Populations" @default.
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• W2494038574 doi "https://doi.org/10.1016/b978-012154351-8/50027-7" @default.
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