the relationship between neural networks and dea-r (case study: companies stock exchange)

نویسندگان

maryam eslamshoar

mohammad reza mozaffari

چکیده

evaluate the performance of companies on the stock exchange using non-parametric methods is very important. dea and dea-r with the strategies for piecewise linear frontier production function and use of available data, assess the stock company. in this study, using a neural network algorithm dea and dea-r is suggested to classify the first companies in the stock exchange; secondly, using the cover models in the nature of input in technology and constant returns to scale non-decreasing scale performance on each floor with propagation neural network is calculated. thirdly, neural network training and repetition, scale efficiency is determined at the end of a functional study is presented on the company's stock.

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عنوان ژورنال:
international journal of data envelopment analysis

ISSN 2345-458X

دوره 3

شماره 2 2015

کلمات کلیدی

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