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| Neural network method in parameter sensitivity analysis and its application in engineering |
| Revised:February 28, 2003 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx20046135 |
| KeyWord:sensitivity analysis,neural network,cable|stayed bridge,construction control |
| Chen Taicong Han Dajian~* Su Cheng |
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| Abstract: |
| In system modelling, the parametric sensitivity analysis is known to be the fundamental work. By applying the sensitivity analysis, the obtained quantitative sensitivity indices (the first|order derivative of system output over system parameter) can then be used for ranking different parameters, as well as identifying the important ones. In most practical systems, however, the explicit functional relationship between system parameters and system output is too complex to be derived and as a result, the first|order derivative sensitivity indices are unable to be computed. The common|used simplified method, single source analysis by use of the finite difference algorithm, has the disadvantage of low accuracy due to the rough model. In this paper, an artificial neural network method is studied to compute the sensitivity indices. Two|layer perceptron is the most widely used type of artificial neural network owing to the simple structure and the ability of high|accuracy simulating of any order nonlinear function. From the mathematical relationships between output variables and input parameters in the trained two|layer perceptron, the first|order derivative sensitivity indices can then be deduced in exact mathematical terms of both normalized and raw input/output data. By this artificial neural network method, the sensitivity indices of multiple parameters are able to be computed at one time through uniform and simple formula, regardless of the system characteristic, i.e. static or dynamic, one stage or multiple stages. Numerical results on one simple structure are presented to show the efficiency and reliability of the proposed method. Finally, the proposed method is employed in the parameter study of cable|stayed bridge construction practice, and valuable information about the influences of stiffness parameter and load parameter on construction control targets is obtained. |
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