A Hybrid Algorithm for Clustering of Time Series Data Based on Affinity Search Technique
Time series clustering is an important solution to various problems in numerous fields of research, including business, medical science, and finance. However, conventional clustering algorithms are not practical for time series data because they are essentially designed for static data. This impract...
Saved in:
Main Authors: | Saeed Aghabozorgi, Teh Ying Wah, Tutut Herawan, Hamid A. Jalab, Mohammad Amin Shaygan, Alireza Jalali |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2014-01-01
|
Series: | The Scientific World Journal |
Online Access: | http://dx.doi.org/10.1155/2014/562194 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Review of Subsequence Time Series Clustering
by: Seyedjamal Zolhavarieh, et al.
Published: (2014-01-01) -
A Fast Density-Based Clustering Algorithm for Real-Time Internet of Things Stream
by: Amineh Amini, et al.
Published: (2014-01-01) -
Band Selection Algorithm Based on Multi-Feature and Affinity Propagation Clustering
by: Junbin Zhuang, et al.
Published: (2025-01-01) -
Breast Cancer Prediction Using the Affinity Propagation Clustering with Regard to the Weights of Variables
by: Sina Dami, et al.
Published: (2020-09-01) -
Combining hybrid and opaque scintillator techniques in the search for double beta plus decays
by: Manuel Böhlers, et al.
Published: (2025-01-01)