Economic Approach for Stochastic Artificial insemination by Neural Network

Zeynolabedin Tashakori and Farzad Mirzaei

MPRA Paper from University Library of Munich, Germany

Abstract: The most common neural network model is the multi-layer perceptron (MLP). This type of neural network is known as a supervised network because it requires a desired output in order to learn. The goal of this type of network is to create a model that correctly maps the input to the output using historical data so that the model can then be used to produce the output when the desired output is unknown. In this paper, a new MLP is proposed for insemination problem. The result of the proposed method, is shown the high performance beside a very fast respond for the problem. Moreover, the conversion of the error is analyzed by the proposed method. All the simulation and result is done in MATLAB environments.

Keywords: A Multilayer Perceptron (MLP); Neural Network; Targets Train; Neuron; Targets Train (search for similar items in EconPapers)
JEL-codes: L00 (search for similar items in EconPapers)
Date: 2016-10-06
New Economics Papers: this item is included in nep-cmp and nep-ore
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/74339/1/MPRA_paper_74339.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:74339

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().