会计和金融中的人工神经网络:建模问题

J. Coakley, Carol E. Brown
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引用次数: 132

摘要

本文回顾了人工神经网络(ann)应用于会计和财务问题的文献,并总结了这些文献中的“建议”。第一部分回顾了人工神经网络的基本基础,为进一步阐述提供了一个共同的基础,并提出了应用于确定人工神经网络的使用是否适当的标准。论文的第二部分讨论了人工神经网络模型的发展,包括:学习算法的选择,误差和传递函数的选择,体系结构的规范,与体系结构相匹配的数据的准备,以及网络的训练。最后部分给出了一些一般准则,并简要总结了研究进展和开放的研究问题。版权所有©2000约翰威利父子有限公司
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial neural networks in accounting and finance: modeling issues
This article reviews the literature on artificial neural networks (ANNs) applied to accounting and finance problems and summarizes the ‘suggestions’ from this literature. The first section reviews the basic foundation of ANNs to provide a common basis for further elaboration and suggests criteria that should be used to determine whether the use of an ANN is appropriate. The second section of the paper discusses development of ANN models including: selection of the learning algorithm, choice of the error and transfer functions, specification of the architecture, preparation of the data to match the architecture, and training of the network The final section presents some general guidelines and a brief summary of research progress and open research questions. Copyright © 2000 John Wiley & Sons, Ltd.
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