An online cluster analysis method for large-scale protein sequences

Author(s):  
DongMing Tang ◽  
YueFei Zhang ◽  
QingXin Zhu ◽  
Jiang Zhang
2019 ◽  
Vol 9 (20) ◽  
pp. 4262 ◽  
Author(s):  
Sitong Lv ◽  
Jianguo Li ◽  
Yongxin Guo ◽  
Zhong Shi

In recent years, distributed generation (DG) technology has developed rapidly. Renewable energy, represented by wind energy and solar energy, has been widely studied and utilized. In order to give full play to the advantages of distributed generation and to meet the challenges of DG access to the power grid, the multi-scenario analysis method commonly used in DG optimal allocation method is studied in this paper. In order to solve the problems that may arise from using large-scale scenes in the planning of DG considering uncertainties by using multi-scene analysis method, the cluster analysis method suitable for large-scale scene reduction in scene reduction method is introduced firstly, and then an improved clustering algorithm is proposed. The validity of the scene reduction method is tested, and the feasibility of the reduction method is verified. Finally, the method mentioned in this paper is compared with other commonly used methods through IEEE-33 node system.


2011 ◽  
Vol 22 (8) ◽  
pp. 1827-1837 ◽  
Author(s):  
Dong-Ming TANG ◽  
Qing-Xin ZHU ◽  
Fan YANG ◽  
Ke CHEN

1995 ◽  
pp. 129-144
Author(s):  
Michel T. Semertzidis ◽  
Etienne Thoreau ◽  
Anne Tasso ◽  
Bernard Henrissat ◽  
Isabelle Callebaut ◽  
...  

2010 ◽  
Vol 41 (2) ◽  
pp. 126-133 ◽  
Author(s):  
N. Kalamaras ◽  
H. Michalopoulou ◽  
H. R. Byun

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.


2016 ◽  
Vol 4 (2) ◽  
pp. 33-57 ◽  
Author(s):  
Seiya Okubo ◽  
Takaaki Ayabe ◽  
Tetsuro Nishino

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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