基于网格计算的反向传播网络

2012 International Conference on Communication, Information & Computing Technology (ICCICT) Pub Date : 2012-12-31 DOI:10.1109/ICCICT.2012.6398173

Ahlam Ansari, K. Devadkar

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引用次数: 1

摘要

反向传播网络(BPN)是一种应用广泛的神经网络。尽管它在世界范围内被广泛采用，但如果训练数据集和属性的数量增加，它的性能会下降。本文提出了一种利用网格计算提高BPN性能的新方法。使用网格(通过中间件连接的一组不同的资源)可以用于提高BPN的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Grid Computing based Back Propagation Network

Back Propagation Network (BPN) is one of the widely used neural network. Despite of worldwide adoption it suffers from performance degradation if the number of training data set and attributes increase. In this paper, we propose a novel method to improve the performance of BPN using Grid Computing. Using grid a set of disparate resources connected through a middleware can be used for increasing the performance of BPN.

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2012 International Conference on Communication, Information & Computing Technology (ICCICT)

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