Data driven soft sensor development for complex chemical processes using extreme learning machine

Chemical Engineering Research and Design ◽

10.1016/j.cherd.2015.06.009 ◽

2015 ◽

Vol 102 ◽

pp. 1-11 ◽

Author(s):

Yan-Lin He ◽

Zhi-Qiang Geng ◽

Qun-Xiong Zhu

Keyword(s):

Extreme Learning Machine ◽

Soft Sensor ◽

Chemical Processes ◽

Data Driven ◽

Complex Chemical ◽

Sensor Development ◽

Learning Machine

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Soft sensor development for the key variables of complex chemical processes using a novel robust bagging nonlinear model integrating improved extreme learning machine with partial least square

Chemometrics and Intelligent Laboratory Systems ◽

10.1016/j.chemolab.2015.12.010 ◽

2016 ◽

Vol 151 ◽

pp. 78-88 ◽

Author(s):

YanLin He ◽

ZhiQiang Geng ◽

QunXiong Zhu

Keyword(s):

Extreme Learning Machine ◽

Nonlinear Model ◽

Soft Sensor ◽

Chemical Processes ◽

Partial Least Square ◽

Least Square ◽

Complex Chemical ◽

Sensor Development ◽

Key Variables ◽

Learning Machine

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An enhanced extreme learning machine with a double parallel structure and its application to modeling complex chemical processes

2017 11th Asian Control Conference (ASCC) ◽

10.1109/ascc.2017.8287605 ◽

2017 ◽

Author(s):

He Yanlin ◽

Wang Pingjiang ◽

Geng Zhiqiang ◽

Han Yongming ◽

Sheng Hao ◽

...

Keyword(s):

Extreme Learning Machine ◽

Chemical Processes ◽

Parallel Structure ◽

Complex Chemical ◽

Learning Machine

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An improved extreme learning machine integrated with nonlinear principal components and its application to modeling complex chemical processes

Applied Thermal Engineering ◽

10.1016/j.applthermaleng.2017.11.061 ◽

2018 ◽

Vol 130 ◽

pp. 745-753 ◽

Author(s):

Qun-Xiong Zhu ◽

Xiao Wang ◽

Yan-Lin He ◽

Yuan Xu

Keyword(s):

Extreme Learning Machine ◽

Principal Components ◽

Chemical Processes ◽

Complex Chemical ◽

Learning Machine

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Energy optimization and analysis modeling based on extreme learning machine integrated index decomposition analysis: Application to complex chemical processes

Energy ◽

10.1016/j.energy.2016.12.090 ◽

2017 ◽

Vol 120 ◽

pp. 67-78 ◽

Author(s):

Zhiqiang Geng ◽

Xiao Yang ◽

Yongming Han ◽

Qunxiong Zhu

Keyword(s):

Extreme Learning Machine ◽

Energy Optimization ◽

Decomposition Analysis ◽

Chemical Processes ◽

Complex Chemical ◽

Index Decomposition Analysis ◽

Integrated Index ◽

Index Decomposition ◽

Analysis Application ◽

Learning Machine

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A new Self-Organizing Extreme Learning Machine soft sensor model and its applications in complicated chemical processes

Engineering Applications of Artificial Intelligence ◽

10.1016/j.engappai.2017.03.011 ◽

2017 ◽

Vol 62 ◽

pp. 38-50 ◽

Author(s):

Zhiqiang Geng ◽

Jungen Dong ◽

Jie Chen ◽

Yongming Han

Keyword(s):

Extreme Learning Machine ◽

Soft Sensor ◽

Chemical Processes ◽

Sensor Model ◽

Learning Machine ◽

Self Organizing

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Novel soft sensor development using echo state network integrated with singular value decomposition: Application to complex chemical processes

Chemometrics and Intelligent Laboratory Systems ◽

10.1016/j.chemolab.2020.103981 ◽

2020 ◽

Vol 200 ◽

pp. 103981 ◽

Author(s):

Yan-Lin He ◽

Ye Tian ◽

Yuan Xu ◽

Qun-Xiong Zhu

Keyword(s):

Singular Value Decomposition ◽

Soft Sensor ◽

Singular Value ◽

Chemical Processes ◽

Echo State Network ◽

Complex Chemical ◽

Sensor Development ◽

Value Decomposition

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Data-driven soft-sensor modelling for air cooler system pH values based on a fast search pruned-extreme learning machine

Asia-Pacific Journal of Chemical Engineering ◽

10.1002/apj.2064 ◽

2016 ◽

Vol 12 (2) ◽

pp. 186-195 ◽

Author(s):

Yisha Ye ◽

Jia Ren ◽

Xuehua Wu ◽

Guofu Ou ◽

Haozhe Jin

Keyword(s):

Extreme Learning Machine ◽

Soft Sensor ◽

Data Driven ◽

Fast Search ◽

Ph Values ◽

Sensor Modelling ◽

Learning Machine

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Production prediction and energy-saving model based on Extreme Learning Machine integrated ISM-AHP: Application in complex chemical processes

Energy ◽

10.1016/j.energy.2018.07.077 ◽

2018 ◽

Vol 160 ◽

pp. 898-909 ◽

Author(s):

Zhiqiang Geng ◽

Hongda Li ◽

Qunxiong Zhu ◽

Yongming Han

Keyword(s):

Energy Saving ◽

Extreme Learning Machine ◽

Chemical Processes ◽

Complex Chemical ◽

Model Based ◽

Learning Machine ◽

Production Prediction

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Soft Sensor Development for Nonlinear Industrial Processes Based on Ensemble Just-in-Time Extreme Learning Machine through Triple-Modal Perturbation and Evolutionary Multiobjective Optimization

Industrial & Engineering Chemistry Research ◽

10.1021/acs.iecr.9b03702 ◽

2019 ◽

Vol 58 (38) ◽

pp. 17991-18006 ◽

Author(s):

Bei Pan ◽

Huaiping Jin ◽

Biao Yang ◽

Bin Qian ◽

Zhengang Zhao

Keyword(s):

Multiobjective Optimization ◽

Extreme Learning Machine ◽

Soft Sensor ◽

Industrial Processes ◽

Just In Time ◽

Sensor Development ◽

Evolutionary Multiobjective Optimization ◽

Learning Machine

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Soft-sensor for Mother Liquor Purity in The Industrial Cane Sugar Crystallization Based on Extreme Learning Machine and Particle Swarm Optimization

International Journal of Control and Automation ◽

10.14257/ijca.2014.7.7.33 ◽

2014 ◽

Vol 7 (7) ◽

Author(s):

Yanmei Meng ◽

Haifeng Pang ◽

Jian Chen ◽

Zhihong Tang ◽

Xiaochun Wang

Keyword(s):

Particle Swarm Optimization ◽

Extreme Learning Machine ◽

Mother Liquor ◽

Particle Swarm ◽

Soft Sensor ◽

Swarm Optimization ◽

Learning Machine

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