Detection and Identification Method of Drilling Total Hydrocarbon Gas Based on Infrared Spectroscopy and KL+BP-RBF Algorithm-Reference-Cited by-同舟云学术

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Detection and Identification Method of Drilling Total Hydrocarbon Gas Based on Infrared Spectroscopy and KL+BP-RBF Algorithm

Published:2022 Issue: Volume:71 Page:1-10
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Liang Haibo¹^ORCID,Chen Haifeng¹^ORCID,Guo Jinhong²^ORCID,Zuo Xing³^ORCID

Affiliation:

1. School of Mechatronic Engineering, Southwest Petroleum University, Chengdu, Sichuan, China

2. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China

3. CNPC Chuanqing Drilling Engineering Technology Research Institute, Deyang, Sichuan, China

Funder

National Natural Science Foundation of China (NSFC), China

Science and Technology Cooperation Project of the CNPC-SWPU Innovation Alliance, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09709882.pdf?arnumber=9709882

Reference35 articles.

1. Research on lithology identification method based on mechanical specific energy principle and machine learning theory

2. Early Warning Model of Sports Injury Based on RBF Neural Network Algorithm

3. Fault-Tolerant Active Disturbance Rejection Control of Plant Protection of Unmanned Aerial Vehicles Based on a Spatio-Temporal RBF Neural Network

4. Tool wear prediction in milling based on a GSA-BP model with a multisensor fusion method

5. Multiclass imbalanced learning with one-versus-one decomposition and spectral clustering

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