Price forecasting for real estate using machine learning: A case study on Riyadh city-Reference-Cited by-同舟云学术

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Price forecasting for real estate using machine learning: A case study on Riyadh city

Published:2021-12-02 Issue: Volume: Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Louati Ali¹²^ORCID,Lahyani Rahma³,Aldaej Abdulaziz¹,Aldumaykhi Abdullah¹,Otai Saad¹

Affiliation:

1. Department of Information Systems, College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Al‐Kharj Saudi Arabia

2. SMART Lab, ISG Tunis University of Tunis Tunis Tunisia

3. Operations and Project Management Department, College of Business Alfaisal University Riyadh Saudi Arabia

Funder

Prince Sattam bin Abdulaziz University

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6748

Reference38 articles.

1. A hybridization of deep learning techniques to predict and control traffic disturbances

2. Deep convolutional neural network architecture design as a bi-level optimization problem

3. LouatiH BechikhS LouatiA AldaejA SaidLB.Evolutionary optimization of convolutional neural network architecture design for thoracic X‐ray image classification. Proceedings of the International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems; 2021:121‐132; Springer Cham.

4. Multi-agent deep neural networks coupled with LQF-MWM algorithm for traffic control and emergency vehicles guidance

5. Deep learning and case-based reasoning for predictive and adaptive traffic emergency management

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