GENETIC ALGORITHMS AND CROSS-CORRELATION CLUSTERING OF TIME SERIES
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Summary
A suitable internal criterion for evaluating the computed partition is presented, and its maximisation by means of a genetic algorithm is proposed.
- Type
- article
- Published
- 2007-01-01
- Cited by
- 1
- References
- 35
- OpenAlex
- https://openalex.org/W11653780
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:16579330
Keywords
Cluster analysis, Series (stratigraphy), Algorithm, Partition (number theory), Mathematics
References
- The percentage points of the normal distribution
- Minimum Spanning Trees and Single Linkage Cluster Analysis
- Solving Partitioning Problems with Genetic Algorithms
- AllelesLociand the Traveling Salesman Problem
- Genetic Algorithms and Grouping Problems
- Clustering of time series with genetic algorithms
- Applying Adaptive Algorithms to Epistatic Domains
- An algorithm for generating artificial test clusters
- An examination of procedures for determining the number of clusters in a data set
- An Introduction to Genetic Algorithms.
- Time series analysis, forecasting and control
- A monte carlo study of thirty internal criterion measures for cluster analysis
- A cautionary note on using internal cross validation to select the number of clusters
- New stopping criterion for genetic algorithms
- Genetic algorithm-based clustering technique
- A genetic clustering algorithm for data with non-spherical-shape clusters
- P-Complete Approximation Problems
- A genetic c-Means clustering algorithm applied to color image quantization
- A DISTANCE MEASURE FOR CLASSIFYING ARIMA MODELS
- Una nota sulla distanza tra modelli ARIMA per serie storiche correlate
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