Predicting Ireland House Prices with Deep Learning Techniques - A Comparative Study

Christopher, Nithish (2024) Predicting Ireland House Prices with Deep Learning Techniques - A Comparative Study. Masters thesis, Dublin, National College of Ireland.

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Abstract

The Republic of Ireland is one of the developed countries in the world. The rapid growth of the housing market is a significant factor in Ireland’s economic development. In recent years, the housing crisis and the increasing house prices have become prominent issues in Ireland, as reported by the Irish Central Newsletter. This research aims at developing a predictive model for the gradual increase in house prices in the Republic of Ireland using deep learning, focusing on historical data analysis from recent years. The data for this study was collected from the Property Price Register Ireland dataset, covering the period from 2010 to 2021. The research focuses on developing and comparing deep learning models, which includes Convolutional Neural Networks (CNN), Artificial Neural Networks (ANN), Long Short-Term Memory Networks (LSTM) and Recurrent Neural Networks (RNN), to identify the best model for predicting house prices. Among these models, the Artificial Neural Networks (ANN) performed the best, based on the RMSE value.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Sahni, Anu UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science H Social Sciences > HD Industries. Land use. Labor > Housing J Political Science > JN Political institutions (Europe) > Ireland Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	02 Sep 2025 09:46
Last Modified:	02 Sep 2025 09:46
URI:	https://norma.ncirl.ie/id/eprint/8688

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