[1]XU Tengteng,WANG Rui,HUANG Hengjun.Curve clustering algorithms by adding the differences among clusters[J].CAAI Transactions on Intelligent Systems,2019,14(2):362-368.[doi:10.11992/tis.201709029]
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Curve clustering algorithms by adding the differences among clusters
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
14
Number of periods:
2019 2
Page number:
362-368
Column:
学术论文—机器学习
Public date:
2019-03-05
- Title:
- Curve clustering algorithms by adding the differences among clusters
- CLC:
- TP181
- DOI:
- 10.11992/tis.201709029
- Abstract:
- With the improvement of accuracy and frequency of data collection, functional data has appeared. Curves’ clustering is a fundamental exploratory task in functional data analysis, and To sovave currently curves clustering algorithms available are based on the differences within each cluster, which has resulted in a low distinction among different curves. Therefore, on the base of curve fitting and curve distance, and with constructed objective function, curves clustering algorithms will be put forward with the consideration of cluster differences. Simulated results show that the curve cluster improves clustering accuracy. The example analysis of hourly NO2 concentration (μg/m3) indicates that this kind of curves clustering algorithms has a better distinction among different clusters.
- References:
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Last Update:
2019-04-25