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| Thermal conductivity function estimation approach based on improved quantum-behavior particle swarm optimization algorithm |
| Received:March 22, 2021 Revised:May 06, 2021 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx20210322002 |
| KeyWord:thermal conductivity function estimation inversion method improved quantum-behavior particle swarm optimization algorithm multi-round upgrading strategy search efficiency |
| Author | Institution |
| 席振翔 |
北京科技大学 能源与环境工程学院, 北京 |
| 于帆 |
北京科技大学 能源与环境工程学院, 北京 |
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| Abstract: |
| In this paper,the improved quantum-behavior particle swarm optimization algorithm is applied to the estimation of thermal conductivity function of materials,and a multi-round upgrading strategy is proposed to optimize the search process of the algorithm,which forms a robust and efficient inversion method. The performance of this method under measurement errors and system errors is tested by numerical experiment,and the performance of different particle swarm optimization algorithms is compared and studied. The results show that the inversion method presented in this paper can converge stably in a large search range and dimension,and has low sensitivity to measurement errors.The multi-round upgrading strategy can improve the searching efficiency of various kinds of particle swarm optimization algorithms in thermal conductivity function estimation problems. |