دانلود مقاله ISI انگلیسی شماره 46067
عنوان فارسی مقاله

استفاده از الگوریتم مدل های ژنتیکی مبتنی پالایش دانش برای پیش بینی سیاست تقسیم سود

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
46067 2012 8 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Using genetic algorithm based knowledge refinement model for dividend policy forecasting
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 39, Issue 18, 15 December 2012, Pages 13472–13479

کلمات کلیدی
سیاست تقسیم سود - الگوریتم های مبتنی بر قانون - الگوریتم ژنتیک - پالایش دانش -
پیش نمایش مقاله
پیش نمایش مقاله استفاده از الگوریتم مدل های ژنتیکی مبتنی پالایش دانش برای پیش بینی سیاست تقسیم سود

چکیده انگلیسی

Dividend policy is one of most important managerial decisions affecting the firm value. Although there are many studies regarding decision-making problems, such as credit policy decisions through bankruptcy prediction and credit scoring, there is no research, to our knowledge, about dividend prediction or dividend policy forecasting using machine learning approaches in spite of the significance of dividends. For dealing with the problems involved in literature, we suggest a knowledge refinement model that can refine the multiple rules extracted through rule-based algorithms from dividend data sets by utilizing genetic algorithm (GA). The new technique, called “GAKR (genetic algorithm knowledge refinement)”, aims to combine the advantages of both knowledge consolidation and GA. The main result of the cross-validation procedure is the average accuracy rate of prediction in the five sets over the five iterations. The experiments show that GAKR model always outperforms other models in the performance of dividend policy prediction; we can predict future dividend policy more correctly than any other models. The major advantages of GAKR model can be summarized as follows: (1) Classification process of GAKR can be very fast with a compact set of rules. In other words, fast training mechanism of GAKR is possible regardless of data set sizes. (2) Multiple rules extracted by GAKR development process are much simpler and easier to understand. Moreover, GAKR model can discriminate redundant rules and inconsistent rules.

خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.