Asia Pacific Academy of Science Pte. Ltd. (APACSCI) specializes in international journal publishing. APACSCI adopts the open access publishing model and provides an important communication bridge for academic groups whose interest fields include engineering, technology, medicine, computer, mathematics, agriculture and forestry, and environment.
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.
OLD city space from the perspective of multi community — Take a floating population community in H city as an example
Vol 1, Issue 1, 2020
Issue release: 31 December 2020
VIEWS - 3098 (Abstract)
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Abstract
Taking the specific practice of an old city space as an example, this paper distinguishes the positions and practices of three actors in the space: Urban planners, managers and ordinary citizens hold an extreme modernist position, firmly believing that the old urban space needs to be removed and transformed into a new urban order; Citizens living in the old city space hold a more complex and contradictory position. As the bottom group of the city, they pay attention to the exchange value of community space, but it is difficult to change their living conditions, while maintaining the exclusion of the old city space and the floating population; The floating population builds the old urban space into a space for production and life, making it a "settled community" entering the city. Finally, the diverse position and practice of the old city space show its significance of urbanization and its important role in the construction of urban diversity.
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Prof. Mehmet Cetin
Kastamonu University,
Turkey
