Abstract
Sheltered housing is a popular living form designed for the elderly in the UK. By simulating and predicting some indicators of sheltered housing, vie can draw on the experience of the UK to help improve the pension system in China. First, sheltered housing is introduced in four aspects including the origin and development, the architectural features, the characteristics of scale and the characteristics of location and vie also clarify the purpose of the paper in the introduction section. Second, the basic theory of support vector machine is presented. Third, vie predict with SVM and PC A several indicators, such as distances from downtown, built cities and quantities of rooms. Finally, vie arrive at the conclusion that SVM is more suitable for predicting the scale and location of sheltered housing.
| Original language | English |
|---|---|
| Pages (from-to) | 129-142 |
| Number of pages | 14 |
| Journal | International Journal of Innovative Computing, Information and Control |
| Volume | 13 |
| Issue number | 1 |
| State | Published - 1 Feb 2017 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- Chinese pension
- Prediction
- Sheltered housing
- Support vector machine
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