Missing data of quality inspection imputation algorithm base on stacked denoising auto-encoder

Analyzing and processing big data of quality inspection is the key factor in ensuring product quality and People's property security. Big data of quality inspection collected by social network and E-commerce is missing in most cases. And the incompleteness of data brings huge challenge for anal...

Full description

Saved in:
Bibliographic Details
Published in2017 IEEE 2nd International Conference on Big Data Analysis (ICBDA) pp. 84 - 88
Main Authors Xiuli Ning, Yingcheng Xu, Xiaohong Gao, Ying Li
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2017
Subjects
Algorithm design and analysis
Big Data
Big data of quality inspection
Clustering algorithms
Filling
Filling algorithm
Inspection
Noise reduction
Stacked denoising auto-encoder
Training
Online AccessGet full text
ISBN9781509036189
1509036180
DOI10.1109/ICBDA.2017.8078781

Cover

More Information
Summary:Analyzing and processing big data of quality inspection is the key factor in ensuring product quality and People's property security. Big data of quality inspection collected by social network and E-commerce is missing in most cases. And the incompleteness of data brings huge challenge for analyzing and processing. Therefore, the algorithm of data filling based on stacked denoising auto-encoder is proposed in this text. As the experiment shows that the algorithm proposed in this text is effective in dealing with big data of quality inspection.
ISBN:9781509036189
1509036180
DOI:10.1109/ICBDA.2017.8078781