Development of a Novel Soft Sensor with Long Short-Term Memory Network and Normalized Mutual Information Feature Selection
Joint Authors
Li, Dongfeng
Li, Zhirui
Sun, Kai
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-04-25
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
In this paper, a novel soft sensor is developed by combining long short-term memory (LSTM) network with normalized mutual information feature selection (NMIFS).
In the proposed algorithm, LSTM is designed to handle time series with high nonlinearity and dynamics of industrial processes.
NMIFS is conducted to perform the input variable selection for LSTM to simplify the excessive complexity of the model.
The developed soft sensor combines the excellent dynamic modelling of LSTM and precise variable selection of NMIFS.
Simulations on two actual production datasets are used to demonstrate the performance of the proposed algorithm.
The developed soft sensor could precisely predict the objective variables and has better performance than other methods.
American Psychological Association (APA)
Li, Dongfeng& Li, Zhirui& Sun, Kai. 2020. Development of a Novel Soft Sensor with Long Short-Term Memory Network and Normalized Mutual Information Feature Selection. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1200632
Modern Language Association (MLA)
Li, Dongfeng…[et al.]. Development of a Novel Soft Sensor with Long Short-Term Memory Network and Normalized Mutual Information Feature Selection. Mathematical Problems in Engineering No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1200632
American Medical Association (AMA)
Li, Dongfeng& Li, Zhirui& Sun, Kai. Development of a Novel Soft Sensor with Long Short-Term Memory Network and Normalized Mutual Information Feature Selection. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1200632
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1200632