Search Result

1

Combustion state recognition of SOFC combustor

一种SOFC燃烧室燃烧状态识别方法

Wang Yang

Fu Xiaowei

Li Xi

solid oxide fuel cell(SOFC)

convolutional neural network

mixed attention mechanism

lightweight network

image feature pyramid

No. 8, 2023 : 2531-2536 doi:10.19734/j.issn.1001-3695.2022.11.0778

2

Research on equipment life prediction based on machine learning combined algorithm under unknown small sample unbalanced data

陌生小样本不平衡数据下基于机器学习联合算法的设备寿命预测研究

Chen Yang

Liu Qinming

Liang Yaoxu

state recognition

SMOTE

PSO

K-means

AdaBoost

residual life prediction

small sample

No. 11, 2021 : 3366-3370,3375 doi:10.19734/j.issn.1001-3695.2021.04.0119

3

Equipment health prognosis based on IPSO-BSVM under small and imbalanced sample data

基于IPSO-BSVM的小样本数据不均衡下的设备健康预测研究

Wei Jingjing

Liu Qinming

Ye Chunming

Chen Xiang

state identification

residual useful life prognosis

small sample

balanced support vector machine(BSVM)

PSO

No. 4, 2021 : 1119-1122,1127 doi:10.19734/j.issn.1001-3695.2020.04.0088

4

Rice seedling status recognition based on machine vision algorithm

基于机器视觉算法的水稻秧苗状态识别

Chen Xinxin

Wang Fulin

Song Yingying

leggy seedlings

state monitoring

visual technology

No. 5, 2019 : 1592-1596 doi:10.19734/j.issn.1001-3695.2017.12.0837

5

Application of PCA+CHMM in equipment performance degradation state recognition

PCA+CHMM在设备性能退化状态识别中的应用研究

Zhong Fei

Ning Qian

Zhou Xinzhi

Zhao Chengping

performance degradation

principal component analysis

continuous hidden Markov model

feature dimensionality reduction

degenerate state recognition

No. 1, 2019 : 136-139 doi:10.19734/j.issn.1001-3695.2017.07.0679

Search 状态识别

Search状态识别returned 5 results

Combustion state recognition of SOFC combustor

Research on equipment life prediction based on machine learning combined algorithm under unknown small sample unbalanced data

Equipment health prognosis based on IPSO-BSVM under small and imbalanced sample data

Rice seedling status recognition based on machine vision algorithm

Application of PCA+CHMM in equipment performance degradation state recognition