ارائه مدلی برای پیش بینی سودآوری شرکت های داروسازی با استفاده از شبکه عصبی مصنوعی

محورهای موضوعی : مدیریت صنعتی

Ali Habibi ¹ , Ghaffar Tari ²

1 - M.A. Student, Tabriz Branch, Islamic Azad University, Tabriz, Iran
2 - Assistant Professor, Marand Branch, Islamic Azad University, Marand, Iran

تاریخ دریافت : 1395/03/02 تاریخ پذیرش : 1395/06/28 تاریخ انتشار : 1395/06/18

کلید واژه: Artificial Neural Network, سودآوری, profitability, Modeling, شبکه عصبی مصنوعی, مدل سازی, Pharmaceutical Companies, شرکت های داروسازی,

چکیده مقاله :

هدف این تحقیق تدوین مدلی برای پیشبینی سودآوری شرکتهای داروسازی با استفاده از شبکه عصبی مصنوعی میباشد. روش تحقیق توصیفی- مدلسازی بوده و جامعه آماری این تحقیق کلیه شرکتهای داروسازی فعال عضو بورس اوراق بهادار به تعداد 21 شرکت میباشد. با توجه به محدود بودن جامعه آماری، هیچ گونه نمونهگیری انجام نشده و کل جامعه مورد پیمایش قرار گرفته است. برای جمع آوری دادهها از اسناد و مدارک شرکتهای داروسازی پذیرفته شده در بورس اوراق بهادار تهران و برای تجزیه وتحلیل دادهها از شبکه عصبی مصنوعی استفاده شده است. نتایج بررسیها نشان میدهد که بهترین مدل پیشبینی سودآوری شرکتهای داروسازی با در نظر گرفتن متغیرهای سرمایه در گردش به کل داراییها، سود(زیان) انباشته به کل داراییها، سود قبل از بهره و مالیات به کل داراییها، ارزش بازار حقوق صاحبان سهام به ارزش دفتری بدهیها، فروش به کل داراییها و نقدینگی بدست آمده است.

چکیده انگلیسی:

The aim of this paper is to develop a model to predict the profitability of pharmaceutical companies using the artificial neural network. The research method was descriptive-modeling and statistical population included all active pharmaceutical companies of the Stock Exchange including 21 companies. Due to the limited population, no sampling was performed and the whole community was surveyed. The documents of pharmaceutical companies were used to data collection and artificial neural networks were used for data analysis. The results showed that the best model to predict the profitability of pharmaceutical companies is obtained by considering the variables of working capital to total assets, cumulative profit (loss) to total assets, earnings before interest and taxes to total assets, the market value of equity to the book value of debts, sales to total assets and liquidity.

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