Finding specific peaks (markers) using fuzzy divisive hierarchical associative-clustering based on the chromatographic profiles of medicinal plant extracts obtained at various detection wavelengths

2020 ◽  
Vol 12 (25) ◽  
pp. 3260-3267
Author(s):  
Ileana M. Simion ◽  
Augustin-C. Moţ ◽  
Costel Sârbu

Advanced chemometric methods, such as fuzzy c-means (FCM), a fuzzy divisive hierarchical clustering algorithm (FDHC), and fuzzy divisive hierarchical associative-clustering (FDHAC), have been successfully applied in this study.

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Zhenghua Hu ◽  
Kejie Huang ◽  
Enyou Zhang ◽  
Qi’ang Ge ◽  
Xiaoxue Yang

Traveling by bike-sharing systems has become an indispensable means of transportation in our daily lives because green commuting has gradually become a consensus and conscious action. However, the problem of “difficult to rent or to return a bike” has gradually become an issue in operating the bike-sharing system. Moreover, scientific and systematic schemes that can efficiently complete the task of rebalancing bike-sharing systems are lacking. This study aims to introduce the basic idea of the k-divisive hierarchical clustering algorithm. A rebalancing strategy based on the model of level of detail in combination with genetic algorithm was proposed. Data were collected from the bike-sharing system in Ningbo. Results showed that the proposed algorithm could alleviate the problem of the uneven distribution of the demand for renting or returning bikes and effectively improve the service from the bike-sharing system. Compared with the traditional method, this algorithm helps reduce the effective time for rebalancing bike-sharing systems by 28.3%. Therefore, it is an effective rebalancing scheme.


Planta Medica ◽  
2010 ◽  
Vol 76 (12) ◽  
Author(s):  
E Sofic ◽  
M Salihovic ◽  
S Huseinovic ◽  
S Cavar ◽  
A Copra-Janicijevic ◽  
...  

Planta Medica ◽  
2012 ◽  
Vol 78 (11) ◽  
Author(s):  
P Taylor ◽  
M Arsenak ◽  
MJ Abad ◽  
Á Fernández ◽  
R Gonto ◽  
...  

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