scholarly journals A Random Line-Search Optimization Method via Modified Cholesky Decomposition for Non-linear Data Assimilation

Author(s):  
Elias D. Nino-Ruiz
2008 ◽  
Vol 16 (5) ◽  
pp. 900-909 ◽  
Author(s):  
Peng Liu ◽  
Cong Liu ◽  
Hui Jiang ◽  
Frank Soong ◽  
Ren-Hua Wang

2010 ◽  
Vol 34 (8) ◽  
pp. 1984-1999 ◽  
Author(s):  
Ahmadreza Zamani ◽  
Ahmadreza Azimian ◽  
Arnold Heemink ◽  
Dimitri Solomatine

2021 ◽  
Vol 30 (2) ◽  
pp. 354-364
Author(s):  
Firas Al-Mashhadani ◽  
Ibrahim Al-Jadir ◽  
Qusay Alsaffar

In this paper, this method is intended to improve the optimization of the classification problem in machine learning. The EKH as a global search optimization method, it allocates the best representation of the solution (krill individual) whereas it uses the simulated annealing (SA) to modify the generated krill individuals (each individual represents a set of bits). The test results showed that the KH outperformed other methods using the external and internal evaluation measures.


1973 ◽  
Vol 99 (1) ◽  
pp. 19-31
Author(s):  
Ying-San Lai ◽  
Jan D. Achenbach

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