scholarly journals An Application of Cluster Analysis Method to Determine Vietnam Airlines’ Ground Handling Service Quality Benchmarks

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Tien-Chin Wang ◽  
Yen Thi Hong Pham
Keyword(s):  
Cluster Analysis ◽  
Service Performance ◽  
Analysis Method ◽  
Service Network ◽  
Productivity Level ◽  
Service Areas ◽  
Cluster Analysis Method ◽  
Ground Handling ◽  
Post Hoc ◽  
The Given

This paper recommends that Vietnam Airlines use a pro-offered model to both evaluate and improve its current service network being operated at international airports. The model includes cluster analysis, ANOVA, and Scheffé post hoc to provide service performance insights and to serve as a complementary corporate benchmark for evaluating service potential and for identifying deficient service areas. By means of this model, the managerial board can designate a potent strategy for ground handling service. Additionally, the given model provides expatriate station managers with a clearer viewpoint of the localized productivity level as performed in relation to other airports concomitant within their own clusters.

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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