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.
Enhancing the visual landscape harmony in public open spaces: Sana’a city case study
Vol 5, Issue 1, 2024
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Abstract
Increasing the visual image quality of public spaces helps enhance the quality of people’s lives. Although previous literature has discussed many of the principles and criteria of the visual design of open environments, architects, landscape architects, and urban designers still face difficulties in defining the most important visual design principles that enhance the Visual Landscape Harmony. This study examined the principles of the visual design of open spaces and their impact on creating a harmonious visual image and raising the quality of the visual landscape. The study mainly used the principles of visual design referred to by Bell. A visual survey analysis of four public spaces in Sana’a city in Yemen was carried out. The study also examined how the selected spaces meet the principles of visual design and their impact on raising the visual quality. Results indicated that the hierarchy, enclosure, figure and ground, diversity in elements, diversity in scales, homogeneous balance of 3D composition, and unique design of the space are the most contributing factors in creating visual harmony and enhancing the quality of the visual image. These principles can help architects, landscape architects, and urban designers and developers to make appropriate design decisions that can produce visual landscape images of open spaces, thus, enhancing the quality of the visual image and the efficiency of urban spaces and open areas.
Keywords
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Prof. Mehmet Cetin
Kastamonu University,
Turkey
