Combinatorial Optimization Method Based on Evaluation of Proximate Optimality Using Correlation Coefficient

2015 ◽  
Vol 135 (4) ◽  
pp. 466-467 ◽  
Author(s):  
Masahide Morita ◽  
Hiroki Ochiai ◽  
Kenichi Tamura ◽  
Junichi Tsuchiya ◽  
Keiichiro Yasuda
2018 ◽  
Vol 173 ◽  
pp. 03030
Author(s):  
Ying Qian ◽  
Boying Zheng

In order to improve the precision of functional imaging of cone beam computed tomography (CBCT), this paper firstly uses the dynamic contrast enhancement tomography (DCE-CT) of the white rabbit as the measured object and establishes volume integral model to obtain the projection data. Then the optimization method is used to solve the optimal parameter pairs of the voxel time density curve (TDC). Finally, the results of the perfusion are obtained by the deconvolution method. The results show that the TDC correlation coefficient is 83.99% after, and the maximum of Spearman correlation coefficient of the perfusion parameter is 0.5125, and the projection time consumption is 7.633 seconds through the volume integral model. It can be seen that the volume integral model is closer to the real projection and it can obtain more accurate perfusion data.


Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 233 ◽  
Author(s):  
Zhenhua Di ◽  
Wei Gong ◽  
Yanjun Gan ◽  
Chenwei Shen ◽  
Qingyun Duan

Quantifying a set of suitable physics parameterization schemes for the Weather Research and Forecasting (WRF) model is essential for obtaining highly accurate typhoon forecasts. In this study, a systematic Tukey-based combinatorial optimization method was proposed to determine the optimal physics schemes of the WRF model for 15 typhoon simulations over the Northwest Pacific Ocean, covering all available schemes of microphysics (MP), cumulus (CU), and planetary boundary layer (PBL) physical processes. Results showed that 284 scheme combination searches were sufficient to find the optimal scheme combinations for simulations of track (km), central sea level pressure (CSLP, hPa), and 10 m maximum surface wind (10-m wind, m s−1), compared with the 700 sets of full combinations (i.e., 10 MP × 7 CU × 10 PBL). The decrease in the typhoon simulation error (i.e., root mean square error between simulation and observations) with this optimal scheme combination was 34%, 33.92%, and 25.67% for the track, CSLP, and 10-m wind, respectively. Overall, the results demonstrated that the optimal scheme combination yields reasonable results, and the Tukey-based optimization method is very effective and efficient in terms of computational resources.


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