Input Variable Selection and Structure Optimization for LSTM-Based Soft Sensor With a Dual Nonnegative Garrote Approach

Author:

Sui Lin1ORCID,Sun Kai2ORCID,Ma Junxia1ORCID,Wang Jiayu1ORCID,Xiong Weili1ORCID

Affiliation:

1. School of Internet of Things Engineering, Jiangnan University, Wuxi, China

2. School of Electrical Engineering and Automation, Shandong Academy of Sciences, Qilu University of Technology, Jinan, China

Funder

National Natural Science Foundation of China

National First-Class Discipline Program of Light Industry Technology and Engineering

111 Project

Postgraduate Research and Practice Innovation Program of Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Reference41 articles.

1. Design of neural networks using genetic algorithm for on-line property estimation of crude fractionator products

2. Neuron-specific dropout: A deterministic regularization technique to prevent neural networks from overfitting & reduce dependence on large training samples;shunk;arXiv 2201 06938,2022

3. ANN-based soft-sensor for real-time process monitoring and control of an industrial polymerization process

4. Dropout: A simple way to prevent neural networks from overfitting;srivastava;J Mach Learn Res,2014

5. Consistent cross-validatory model-selection for dependent data: hv-block cross-validation

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