| Zeit: | 22. Mai 2019 |
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| Download als iCal: |
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14:00-15:00, ITI-Seminarraum 3.175,
Institut für Technische Informatik
Adaptive testing is a promising approach that prac-tically ensures cost reduction and reliability for test strategy. In adaptive testing, the test content or pass/fail limits are not fixed as in conventional test, but depend on other test results of the currently or historically tested data. Based on recent progress in machine learning, a new Long Short-Term Memory (LSTM) which is more advanced than simple Recurrent Neuron Network (RNN) is proposed for defect screening. The simulation results have been compared with the other deep learning and traditional methods when patterns are increased and decreased. The comparisons show that the proposed RNN-based LSTM method has achieved remarkable improvements.