تبیین دسته بندهای ماشین بردار پشتیبان و شبکه عصبی جهت درجه بندی شعب بانک

فصلنامه مدیریت راهبردی در سیستم های صنعتی (مدیریت صنعتی سابق)

دوره 15، شماره 53، آبان 1399، صفحه 53-70   

نوع مقاله: مقاله پژوهشی

نویسندگان

داود خسروانجم^{* 1}؛ محمد الیاسی²؛ بهزاد کشانچی³؛ بهاره بوبانیان⁴؛ شوانه عبدالهی⁵

¹تهران، دانشگاه تربیت مدرس، گروه آموزشی مدیریت

²کارشناس ارشد مهندسی نرم افزار گرایش هوش مصنوعی

³گروه مدیریت بانکی,دانشکده علوم اقتصادی، موسسه علوم بانکی ,تهران, ایران

⁴گروه مدیریت بازرگانی، دانشکده مدیریت، واحد سنندج، دانشگاه آزاد اسلامی، سنندج، ایران

⁵گروه مدیریت دولتی,دانشکده مدیریت، واحدمهاباد،دانشگاه آزاد اسلامی ,مهاباد, ایران

چکیده

در صنعت بانکداری اطلاعات زیادی وجود دارد که شناسایی آن از اهمیت ویژه‌ای برخوردار است. استفاده از تکنیک های داده کاوی نه تنها کیفیت را بهبود می بخشد بلکه منجر به مزایای رقابتی و ارتقای جایگاه بازار نیز می گردد. با استفاده از داده کاوی و به منظور تجزیه و تحلیل الگوها و روندها، بانکها می توانند صحت این را پیش بینی کنند درجه بندی شعب بانک چگونه است. در این مقاله درجه بندی شعب یکی از بانکهای بزرگ تجاری (تعداد شعب انتخاب شده 1825 شعبه و تعداد ویژگی های مورد استفاده 57 ویژگی) با استفاده از دسته بندهای ماشین بردار پشتیبان و شبکه عصبی چند لایه پرسپترون برروی داده های واقعی انجام گرفت. نتایج ارزیابی مربوط به ماشین بردار پشتیبان نشان داد که این دسته بند دارای کارایی پایین تری برای روش پیشنهادی است. اما استفاده از شبکه های عصبی و ترکیب آن با PCA نشان داد که دارای معیارهای کارایی بالایی است. مقادیر مربوط به کارایی و صحت با استفاده از شبکه عصبی با دقت بسیار بالایی بدست آمد.

کلیدواژه‌ها

داده کاوی؛ بانکداری؛ ماشین بردار پشتیبان؛ شبکه عصبی

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