DAMP: Decision-Making with the Combination of Analytical Hierarchy Process and Deep Learning (Case study: Car Sales Forecasting)
Publish place: Computer and Knowledge Engineering، Vol: 4، Issue: 2
Publish Year: 1400
نوع سند: مقاله ژورنالی
زبان: English
View: 160
This Paper With 6 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
این Paper در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_CKE-4-2_003
تاریخ نمایه سازی: 25 خرداد 1401
Abstract:
Nowadays, prediction and decision making are two inseparable principles in the management and two distinct roles of managers. The organizations spend a large part of their budgets on predictions from past data. They will lose their money if they are neglected. On the other hand, decision-making is the most critical step in problem-solving. Moreover, it is considered the main task of a manager as a problem solver. Making decision becomes more complicated when we are faced with multi-criteria decision-making issues. Combining prediction and decision-making approaches helps researchers to make a better choice utilizing prior knowledge. One of the most essential and comprehensive systems designed for multi-criteria decision-making is Analytical Hierarchy Process (AHP) process. Deep learning as a valuable extension of artificial neural networks has been the focus of many researchers. In this paper, AHP is used to classify, compare, and determine the weights of a deep learning approach. In order to evaluate the efficiency of the proposed method, the prediction of vehicle price application is chosen, and the results are compared with neural networks. The data set is related to the sale of Hyundai and Kia Motors cars in the United States and Canada. It is emphasized that the data are used only to evaluate the proposed method and can be generalized to solve all similar issues. The sales forecasting data of two car companies showed that the proposed method is superior to other regression methods. To extend the proposed methos as our future work, the aim will be to develop a comprehensive decision-making and forecasting system by combining these two approaches.
Keywords:
Authors
Mostafa Sabzekar
Department of Computer Engineering, Birjand University of Technology, Birjand, Iran.
Farhad Afarideh
Department of Statistics, Allameh Tabataba&#۰۳۹;i University, Tehran, Iran.
Arash Deldari
Department of Computer Engineering, University of Torbat Heydarieh, Torbat Heydarieh, Iran.
Atieh Rezaei
Department of Information and Communication Technology (ICT), Technical and Vocational University (TVU), Tehran, Iran.
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :