دانلود مقاله ISI انگلیسی شماره 48641
عنوان فارسی مقاله

امتیاز دهی اعتباری و اختصاص مجدد موارد مردود از طریق روش های محاسبات تکاملی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
48641 2003 9 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Credit scoring and rejected instances reassigning through evolutionary computation techniques
منبع

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

Journal : Expert Systems with Applications, Volume 24, Issue 4, May 2003, Pages 433–441

کلمات کلیدی
اعتبارسنجی - تقسیم بندی - طبقه بندی معکوس - شبکه های عصبی - الگوریتم های ژنتیکی
پیش نمایش مقاله
پیش نمایش مقاله امتیاز دهی اعتباری و اختصاص مجدد موارد مردود از طریق روش های محاسبات تکاملی

چکیده انگلیسی

The credit industry is concerned with many problems of interest to the computation community. This study presents a work involving two interesting credit analysis problems and resolves them by applying two techniques, neural networks (NNs) and genetic algorithms (GAs), within the field of evolutionary computation. The first problem is constructing NN-based credit scoring model, which classifies applicants as accepted (good) or rejected (bad) credits. The second one is better understanding the rejected credits, and trying to reassign them to the preferable accepted class by using the GA-based inverse classification technique. Each of these problems influences on the decisions relating to the credit admission evaluation, which significantly affects risk and profitability of creditors. From the computational results, NNs have emerged as a computational tool that is well-matched to the problem of credit classification. Using the GA-based inverse classification, creditors can suggest the conditional acceptance, and further explain the conditions to rejected applicants. In addition, applicants can evaluate the option of minimum modifications to their attributes.

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