Mu-Yen Chen and Min-Hsuan Fan and Chia-Chen Chen and Siang-Yu Jhong
Integrating Artificial Neural Network and Taguchi Method on Constructing the Real Estate Appraisal Model
3010 - 3018
2014
8
9
International Journal of Economics and Management Engineering
https://publications.waset.org/pdf/9999425
https://publications.waset.org/vol/93
World Academy of Science, Engineering and Technology
In recent years, real estate prediction or valuation has
been a topic of discussion in many developed countries. Improper
hype created by investors leads to fluctuating prices of real estate,
affecting many consumers to purchase their own homes. Therefore,
scholars from various countries have conducted research in real estate
valuation and prediction. With the backpropagation neural network
that has been popular in recent years and the orthogonal array in the
Taguchi method, this study aimed to find the optimal parameter
combination at different levels of orthogonal array after the system
presented different parameter combinations, so that the artificial
neural network obtained the most accurate results. The experimental
results also demonstrated that the method presented in the study had a
better result than traditional machine learning. Finally, it also showed
that the model proposed in this study had the optimal predictive effect,
and could significantly reduce the cost of time in simulation operation.
The best predictive results could be found with a fewer number of
experiments more efficiently. Thus users could predict a real estate
transaction price that is not far from the current actual prices.
Open Science Index 93, 2014