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Based on a large number of downlink telemetry data during the spacecraft on-orbit operation, the characteristic of spacecraft state change is obtained. It is of great significance to realize the safe and reliable spacecraft operation management. In order to achieve the accurate trend prediction for a spacecraft, a hybrid prediction algorithm using wavelet analysis and time series method is presented...
The robust inferential estimation of syngas compositions using stacked neural network was presented. Data for building non-linear models is re-sampled using bootstrap techniques to form a number of sets of training and test data. For each data set, a neural network model was developed which were then aggregated through principal component regression. To improve the robustness and accuracy of the neural...
A robust inferential estimator model based on improved dynamic principal component analysis (DPCA) and multiple neural networks (MNN) was proposed. Data for building non-linear models was re-sampled using DPCA algorithm to form a number of sets of training and test data. For each data set, a neural network model was developed. To improve the robustness and accuracy of the neural networks, the MNN...
A novel estimator model, which incorporates DPCA (dynamic principal component analysis), RBF (radial basis function) networks, and MSA (multi-scale analysis), is proposed to infer the properties of manufactured products from real process variables. DPCA is carried out to select the most relevant process features and to eliminate the correlations of input variables; multi-scale analysis is introduced...
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