Global sensitivity analysis method for improving usefulness of complex information system
A technology of global sensitivity and information system, applied in neural learning methods, neural architecture, biological neural network models, etc., can solve problems such as low efficiency and poor effect
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[0018] The present invention will be further described below in conjunction with the accompanying drawings and related algorithms.
[0019] The overall process of the present invention is as figure 1 shown.
[0020] The invention analyzes the system simulation data based on the information, and obtains the training samples evenly distributed in the value range of the coverage index by sampling the Latin hypercube. The extreme learning machine is selected as the proxy model, and the optimal proxy model is obtained through training. Select quasi-Monte Carlo sampling instead of traditional Monte Carlo sampling to collect a large amount of data required for global sensitivity analysis, and obtain a complete analysis sample through the proxy model, and analyze the analysis sample set through the Sobol index method to obtain the impact of complex information systems. Sensitive indicators of performance. The specific implementation steps are as follows:
[0021] 1. Efficacy Evalu...
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