Design and Implementation of Housing Price Forecast System Based on Deep Learning
WANG Xiaodong
CHEN Xinlong
LIN Xiaoting
SUN Dongpu
Abstract：With the rapid development of economy,many people are facing the difficulties of buying houses and the high risk of investing in real estate.Housing is a dual problem of housing function and investment utility,so housing prices become more and more complex.There are many factors affecting house prices,and the overall trend is nonlinear.A house price prediction system based on deep learning is designed and implemented,which selects the influencing factors of house price according to the relevant economic principles,processes the data,and uses the data to train and verify the neural network model,so as to achieve the pur-pose of predicting house price.The B/S structure is adopted in the system,and Django is used to build a server.The functions such as house price prediction,data set query,and house price forum are provided in the system.
Keywords：deep learninghousing price predictionDjango
Publication Date：2024-09-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 2572-2576,2650 )