期刊
JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER
卷 133, 期 -, 页码 351-363出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jqsrt.2013.08.020
关键词
Inverse problem; Ant Colony Optimization; Transient radiative transfer; Finite Volume Method
资金
- Foundation for Innovative Research Groups of the National Natural Science Foundation of China [51121004]
- National Nature Science Foundation of China [51076037]
- Specialized Research Fund for the Doctoral Program of Higher Education [20122302110046]
As a heuristic intelligent optimization algorithm, the Ant Colony Optimization (ACO) algorithm was applied to the inverse problem of a one-dimensional (1-D) transient radiative transfer in present study. To illustrate the performance of this algorithm, the optical thickness and scattering albedo of the 1-D participating slab medium were retrieved simultaneously. The radiative reflectance simulated by Monte-Carlo Method (MCM) and Finite Volume Method (FVM) were used as measured and estimated value for the inverse analysis, respectively. To improve the accuracy and efficiency of the Basic Ant Colony Optimization (BACO) algorithm, three improved ACO algorithms, i.e., the Region Ant Colony Optimization algorithm (RACO), Stochastic Ant Colony Optimization algorithm (SACO) and Homogeneous Ant Colony Optimization algorithm (HACO), were developed. By the HACO algorithm presented, the radiative parameters could be estimated accurately, even with noisy data. In conclusion, the HACO algorithm is demonstrated to be effective and robust, which had the potential to be implemented in various fields of inverse radiation problems. (C) 2013 Elsevier Ltd. All rights reserved.
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