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Training a Neural Network to Predict House Rents Using Artifical Intelligence and Deep Learning | IEEE Conference Publication | IEEE Xplore

Training a Neural Network to Predict House Rents Using Artifical Intelligence and Deep Learning


Abstract:

We are training neural networks to predict house rents using artificial intelligence and deep learning, which is being used in the real estate and financial industries. R...Show More

Abstract:

We are training neural networks to predict house rents using artificial intelligence and deep learning, which is being used in the real estate and financial industries. Real estate agents, financial institutions, and real estate developers can benefit from rent forecasting, which is an important application scenario. Many real estate websites now use machine learning models to predict rents to help tenants and landlords find the right rental price. Machine learning models are also being used by some real estate companies and financial institutions to determine rents more accurately. Training neural networks to predict rent is still a relatively new field that needs more research and experimentation to improve its performance and accuracy.
Date of Conference: 11-13 August 2023
Date Added to IEEE Xplore: 27 September 2023
ISBN Information:
Conference Location: Changchun, China

I. Introduction

Rent market transparency can be improved by using neural networks to predict rent. Consumers can better understand the rent market by using a neural network model, which allows them to make better rent-related decisions; landlords and tenants can make smarter decisions; rental market efficiency can be improved: A more accurate forecast of rents will help the rental market allocate resources more efficiently, which will boost its efficiency. Applying neural network technology to predict rents could help the real estate industry respond better to market changes, thereby promoting its growth.

References

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