Abstract
This paper proposes an improved data fusion method for water quality sensors. First, a deep learning network model is formed by stacking automatic encoder and sparse automatic encoder, so as to realize feature mining and sparse representation of sample data. Second, after large-scale sample training, the network model may fit complex nonlinear functions, and has certain generalization ability for low-quality sample data. As a result, the accuracy of prediction and classification can be improved. The experimental results demonstrate that the proposed method can obtain higher classification accuracy.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IOP Conference Series: Earth and Environmental Science
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
