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DC Field | Value | Language |
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dc.contributor.author | Thomas, L. | |
dc.contributor.author | Kumar, M.M.V. | |
dc.contributor.author | Annappa | |
dc.date.accessioned | 2020-03-31T08:18:34Z | - |
dc.date.available | 2020-03-31T08:18:34Z | - |
dc.date.issued | 2016 | |
dc.identifier.citation | Information (Japan), 2016, Vol.19, 10, pp.4611-4615 | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/10074 | - |
dc.description.abstract | The aim of this study was to develop an Artificial Neural Network's recommendation model for an online process using the complexity of load and performance of the resources. The proposed model investigate the resource performance using stochastic gradient decent method and probabilistic cost function for learning ranking function. The test result of CoSeLoG project is presented with accuracy of 72.856%. 2016 International Information Institute. | en_US |
dc.title | Best resource recommendation for a stochastic process | en_US |
dc.type | Article | en_US |
Appears in Collections: | 1. Journal Articles |
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