Domain Transfer Extreme Learning Machine Method Based on Manifold Regularization and Norm Regularization
A technology of extreme learning machine and domain, applied in the field of transfer extreme learning machine algorithm, which can solve the problems of data offset and lack of domain transfer ability.
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[0046] In order to better understand the present invention, the present invention will be further described in detail below in conjunction with specific examples, but the following description is only for demonstration and explanation, and does not limit the present invention in any form.
[0047] The data used in this embodiment comes from the UCI machine learning database. The database contains data of 13,910 gas samples of 6 gases collected by an electronic nose system on a gas transmission platform for 36 consecutive months. In this embodiment, each sample is characterized by extracting a 128-dimensional feature. Since the gas detection sensor of the electronic nose system will have sensor drift with time, the collected gas data will also have data drift in different time periods. The flow process of the inventive method is as figure 1 shown.
[0048] Step 1: Take the data of 445 gas samples in the first and second months as the source field data of the sensorless drift...
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