دوره 20، شماره 4 - ( 12-1402 )
جلد 20 شماره 4 صفحات 66-45 |
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moradi B, Khalaj M, Taghizadeh Harat A. Improved Ensemble Learning Model by Swarm Intelligence for Mobile Subscribers’ Churn Prediction. JSDP 2024; 20 (4) : 4
URL: http://jsdp.rcisp.ac.ir/article-1-1344-fa.html
URL: http://jsdp.rcisp.ac.ir/article-1-1344-fa.html
مرادی بیژن، خلج مهران، تقی زاده هرات علی. الگوی یادگیری جمعی بهبود‌یافته با هوش ازدحامی جهت پیش‌بینی ریزش مشترکان تلفن همراه. پردازش علائم و داده‌ها. 1402; 20 (4) :45-66
دانشگاه ازاد اسلامی واحد پرند و رباط کریم
چکیده: (709 مشاهده)
ازآنجاکه در شرکت‌های مخابرات همراه، هزینۀ حفظ مشتریان فعلی بسیار کمتر از هزینۀ جذب مشتریان جدید است، پیش‌بینی دقیق امکان ریزش هریک از مشتریان و جلوگیری از آن، امری ضروری است. بنابراین، پژوهشگران روش‌های کارآمدی را با استفاده از ابزارهای داده‌کاوی و هوش مصنوعی برای شناسایی مشتریانی که قصد روی‌گردانی دارند، ارائه کرده‌اند. در این مقاله، ما به‌منظور بهبود فرایند پیش‌بینی ریزش مشتری، یک راهکار مؤثر مبتنی‌بر یادگیری جمعی پیشنهاد می‌کنیم که در آن از الگوریتم بهینه‌سازی گرگ خاکستری، به‌منظور انتخاب ویژگی‌های مؤثر و همچنین تنظیم شاخص‌های آزاد الگوی پیشنهادی، استفاده شده‌است. سپس، به‌منظور ارزیابی عملکرد روش پیشنهادی، آن را با استفاده از دو مجموعه‌دادۀ ریزش مشتری شبیه‌سازی کرده و نتایج حاصل را به کمک معیارهای ارزیابی شامل صحت، دقت، یادآوری، امتیاز F1 و AUC با سایر روش‌های مشابه مقایسه کرده‌ایم. نتایج به‌دست‌آمده برتری روش پیشنهادی بر سایر راهکارهای ارزیابی‌شده را نشان می‌دهد.
شماره‌ی مقاله: 4
واژه‌های کلیدی: پیش‌بینی ریزش مشتری، مخابرات همراه، یادگیری جمعی، هوش ازدحامی، الگوریتم بهینه‌سازی گرگ خاکستری
نوع مطالعه: پژوهشي |
موضوع مقاله:
مقالات پردازش داده‌های رقمی
دریافت: 1401/8/3 | پذیرش: 1401/10/5 | انتشار: 1403/2/6 | انتشار الکترونیک: 1403/2/6
دریافت: 1401/8/3 | پذیرش: 1401/10/5 | انتشار: 1403/2/6 | انتشار الکترونیک: 1403/2/6
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