Whole flow field performance prediction by impeller parameters of centrifugal pumps using support vector regression

2017 ◽  
Vol 114 ◽  
pp. 258-267 ◽  
Author(s):  
Hongying Deng ◽  
Yi Liu ◽  
Ping Li ◽  
Shengchang Zhang
2012 ◽  
Vol 630 ◽  
pp. 366-371 ◽  
Author(s):  
Kuo Ping Lin

The success of CPU performance prediction will make many benefits. This study adopts the least-squares support vector regression (LS-SVR) with particle swarm optimization (PSO) algorithm to improver accuracy of CPU performance prediction. LS-SVR with PSO, support vector regression (SVR) with PSO, general regression neural network (GRNN), radial basis neural network (RBNN), and linear regression are employed for CPU performance prediction. Empirical results indicate that the LS-SVR (Linear kernel) with PSO has better performance in terms of forecasting accuracy than the other methods. Therefore, the LS-SVR (Linear kernel) with PSO model can efficiently provide credible CPU performance estimated value.


2016 ◽  
Vol 136 (12) ◽  
pp. 898-907 ◽  
Author(s):  
Joao Gari da Silva Fonseca Junior ◽  
Hideaki Ohtake ◽  
Takashi Oozeki ◽  
Kazuhiko Ogimoto

2020 ◽  
Author(s):  
Avinash Wesley ◽  
Bharat Mantha ◽  
Ajay Rajeev ◽  
Aimee Taylor ◽  
Mohit Dholi ◽  
...  

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