Title :
Research of Refueling customer classifications based on kernel clustering algorithm under the organic combined model
Author_Institution :
Dept. of Equip. & Transp. Eng., Coll. of CAPF, Xi´an, China
Abstract :
The kernel clustering algorithm under the organic combined model of the GA and the PSO was put forward. According to the customers´ data of certain, this kernel clustering algorithm was applied to classify the Refueling customers into three groups: the first group includes 3 customers, 5 and 7 customers for the second group and the third group respectively. The result shows that the samples can be classified and the center of mass can be obtained using the data description based on kernel methods. But the clustering region is different when the σ of kernel method gets the different value. This makes the clustering process to be complex, also spends the longer time. While kernel method´s clustering algorithm organically combined with the PSO and GA can get the same result in the shorter time and the calculation is simpler.
Keywords :
computer software; customer profiles; customer services; genetic algorithms; particle swarm optimisation; pattern clustering; GA model; PSO model; customer data; kernel clustering algorithm; kernel method based data description; organic combined model; refueling customer classification; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Educational institutions; Genetic algorithms; Kernel; Particle swarm optimization; clustering algorithm; kernel methods; particle swarm algorithm; refueling customer;
Conference_Titel :
Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on
Conference_Location :
Jilin
Print_ISBN :
978-1-61284-719-1
DOI :
10.1109/MEC.2011.6025768