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LS-SVM Based Modeling and Forecast of Operator Functional State in a Human-Machine System

Author: QinPanPan
Tutor: ZhangJianHua
School: East China University of Science and Technology
Course: Control Science and Engineering
Keywords: Functional status of the operator Least squares support vector machine Electrophysiological signals Modeling
CLC: TP181
Type: Master's thesis
Year: 2011
Downloads: 71
Quote: 0
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Abstract


The key to an accurate assessment of the functional status of the man-machine system operator ( Operator Functional States , OFS ) is to establish a mathematical model has a strong predictive power . Based on collected a series of operator electrical physiological signals and performance data , using the least squares support vector machine (Least Squares Support Vector Machine, LS-SVM) method on the OFS modeling . By grid search ( Grid Search ) and 10 - fold cross-validation (10-fold cross-validation) method to optimize the model parameters , the lack of standard on LS-SVM , using the Suykens the improvement of the LS-SVM algorithm , the establishment of sparse and robustness of the LS-SVM model , and the LS-SVM and fuzzy modeling method based on genetic algorithm results comparison . The results show that the LS - SVM method has better generalization performance for OFS Rate is valid . According to the predicted results , you can adjust the control strategy , in order to design and implement intelligent human-computer interaction system .

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CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory > Automated reasoning,machine learning
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