Abstract There exist a considerable variety of factors affecting the spectral emissivity of an object. The authors have designed an improved combined neural network emissivity model, which can identify the continuous spectral emissivity and true temperature of any object only based on the measured brightness temperature data. In order to improve the accuracy of approximate calculations, the local minimum problem in the algorithm must be solved.Therefore, the authors design an optimal algorithm, i.e. a hybrid chaotic optimal algorithm, in which the chaos is used to roughly seek for the parameters involved in the model, and then a second seek for them is performed using the steepest descent. The modelling of emissivity settles the problems in assumptive models in multi-spectral theory.
Received: 20 August 2004
Revised: 13 June 2005
Accepted manuscript online:
PACS:
05.45.-a
(Nonlinear dynamics and chaos)
Cite this article:
Yang Chun-Ling (杨春玲), Wang Yu-Ye (王宇野), Zhao Dong-Yang (赵东阳), Zhao Guo-Liang (赵国良) The measuring of spectral emissivity of object using chaotic optimal algorithm 2005 Chinese Physics 14 2041
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