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As China's pillar industry, the property market has suffered a considerable impact in recent years, with a decline in turnover and many developers at risk of bankruptcy. As one of the most concerned factors for stakeholders, housing prices need to be predicted more objectively and accurately to minimize decision-making errors by developers and consumers. Many prediction models in recent years have been unfriendly to consumers due to technical difficulties, high data demand, and varying factors affecting house prices in different regions. A uniform model across the country cannot capture local differences accurately, so this study compares and analyses the fitting effects of multiple machine learning models using February 2024 new building data in Changsha as an example, aiming to provide consumers with a simple and practical reference for prediction methods. The modeling exploration applies several regression techniques based on machine learning algorithms, such as Stepwise regression, Robust regression, Lasso regression, Ridge regression, Ordinary Least Squares (OLS) regression, Extreme Gradient Boosted regression (XGBoost), and Random Forest (RF) regression. These algorithms are used to construct forecasting models, and the best-performing model is selected by conducting a comparative analysis of the forecasting errors obtained between these models. The research found that machine learning is a practical approach to property price prediction, with least squares regression and Lasso regression providing relatively more convincing results.
A place to commemorate Smyrna refugees
Vol 6, Issue 1, 2025
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Abstract
The paper delves into the role and power of places of memory in preserving and strengthening the collective memory and identity of Greeks who originated from Asia Minor and specifically Smyrna. Historical data are presented regarding the persecution of this community and the triptych “place-collective identity-collective memory” is thoroughly studied. Through semi-structured interviews, and participatory design methods, with the collaboration of users, landscape architect, agronomist, and sociologist, the landscape design proposal aims to create the First Nationwide Open-Air Museum of Smyrna in Thessaloniki, Greece. The new land uses are based on the shaping and preservation of the collective memory and identity of Smyrnaeans, and the coexistence of historical and cultural elements in a modern design canvas. Users and visitors perceive the landscape as a document of the Smyrnaean culture, which narrates the history of their community, allowing them to define their particular identity and identify themselves as “us”.
Keywords
References
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Prof. Mehmet Cetin
Kastamonu University,
Turkey
