scholarly journals A hybrid factorial stepwise-cluster analysis method for streamflow simulation – a case study in northwestern China

2016 ◽  
Vol 61 (15) ◽  
pp. 2775-2788 ◽  
Author(s):  
X.W. Zhuang ◽  
Y.P. Li ◽  
G.H. Huang ◽  
X.Q. Wang
Keyword(s):  
Cluster Analysis ◽  
Northwestern China ◽  
Analysis Method ◽  
Cluster Analysis Method ◽  
Stepwise Cluster Analysis ◽  
Streamflow Simulation

Application of Set Pair Analysis in the Material Clustering

2013 ◽  
Vol 443 ◽  
pp. 707-710
Author(s):  
Ya Feng Yang ◽  
Ai Min Yang ◽  
Huan Cheng Zhang
Keyword(s):  
Cluster Analysis ◽  
Fuzzy Set ◽  
Clustering Analysis ◽  
Set Pair Analysis ◽  
Analysis Method ◽  
Clustering Methods ◽  
Analysis Theory ◽  
Cluster Analysis Method ◽  
Pair Analysis

Based on the Set Pair Analysis theory and fuzzy set, the traditional clustering methods were taken into account from the characteristics of the forward, reverse and uncertain factors. A new cluster analysis method was proposed which allows more flexible clustering analysis. A case study in the materials clustering was carried on for the consumers to look for the most benefits in line with their own requirements.

scholarly journals Detection of drought events in Greece using daily precipitation

2010 ◽  
Vol 41 (2) ◽  
pp. 126-133 ◽  
Author(s):  
N. Kalamaras ◽  
H. Michalopoulou ◽  
H. R. Byun
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Daily Precipitation ◽  
Hierarchical Cluster ◽  
Seasonal Distribution ◽  
Drought Severity ◽  
Severe Drought ◽  
Analysis Method ◽  
Cluster Analysis Method ◽  
Insight Into

In this study a method proposed by Byun & Wilhite, which estimates drought severity and duration using daily precipitation values, is applied to data from stations at different locations in Greece. Subsequently, a series of indices is calculated to facilitate the detection of drought events at these sites. The results provide insight into the trend of drought severity in the region. In addition, the seasonal distribution of days with moderate and severe drought is examined. Finally, the Hierarchical Cluster Analysis method is used to identify sites with similar drought features.

Cluster Analysis Using N-gram Statistics for Daihinmin Programs and Performance Evaluations

2016 ◽  
Vol 4 (2) ◽  
pp. 33-57 ◽  
Author(s):  
Seiya Okubo ◽  
Takaaki Ayabe ◽  
Tetsuro Nishino
Keyword(s):  
Cluster Analysis ◽  
Imperfect Information ◽  
Computer Game ◽  
Computer Experiments ◽  
Performance Evaluations ◽  
Analysis Method ◽  
Cluster Analysis Method ◽  
N Gram ◽  
And Performance ◽  
Feature Values

In this paper, the authors elucidate the characteristics of the computer game Daihinmin, a popular Japanese card game that uses imperfect information. They first propose a method to extract feature values using n-gram statistics and a cluster analysis method that employs feature values. By representing the program card hands as several symbols, and the order of hands as simplified symbol strings, they obtain data that is suitable for feature extraction. The authors then evaluate the effectiveness of the proposed method through computer experiments. In these experiments, they apply their method to ten programs that were used in the UEC Computer Daihinmin Convention. In addition, the authors evaluate the robustness of the proposed method and apply it to recent programs. Finally, they show that their proposed method can successfully cluster Daihinmin programs with high probability.

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