Nonlinear curve fitting to stopping power data using RBF neural networks
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- 作者：Michael M. Li<sup> ; sup><sup>m.li@cqu.edu.au" class="auth_mail" title="E-mail the corresponding authorsup> ; Brijesh Verma <sup>b.verma@cqu.edu.au" class="auth_mail" title="E-mail the corresponding authorsup>
- 关键词：Radial basis function ; Neural network ; Curve fitting ; Stopping power
- 刊名：Expert Systems with Applications
- 出版年：2016
- 出版时间：1 March 2016
- 年：2016
- 卷：45
- 期：Complete
- 页码：161-171
- 全文大小：1764 K
文摘
- ss="listitem" id="list_celist0001">
- ss="label">•
ra0001">We present a novel method using an RBF neural network with an additional linear term.
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ra0002">A simple and accurate empirical formula is developed for stopping power data, based on RBF.
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ra0003">A benchmark dataset is tested with the new method.
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ra0004">Additional linear term improves fitting accuracy.
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ra0005">The new method can be used to fit various types of data- many applications in engineering.