Online Estimation of the pH Value for Froth Flotation of Bauxite Based on Adaptive Multiple Neural Networks**Sponsor and financial support: the National Natural Science Foundation of China (61304126, 61304019) and Foundation for Innovative Research Groups of the National Natural Science Foundation of China (61321003), the Ph.D. Programs Foundation of the Education Ministry of China (No. 20120162120022).

Xiao-li Wang; Lei Huang; Peng Yang; Chun-hua Yang; Qi-yue Xie

doi:10.1016/j.ifacol.2016.10.112

Online Estimation of the pH Value for Froth Flotation of Bauxite Based on Adaptive Multiple Neural Networks**Sponsor and financial support: the National Natural Science Foundation of China (61304126, 61304019) and Foundation for Innovative Research Groups of the National Natural Science Foundation of China (61321003), the Ph.D. Programs Foundation of the Education Ministry of China (No. 20120162120022).

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2016.10.112 ◽

2016 ◽

Vol 49 (20) ◽

pp. 149-154 ◽

Cited By ~ 4

Author(s):

Xiao-li Wang ◽

Lei Huang ◽

Peng Yang ◽

Chun-hua Yang ◽

Qi-yue Xie

Keyword(s):

Neural Networks ◽

Natural Science ◽

Financial Support ◽

Ph Value ◽

Froth Flotation ◽

Research Groups ◽

Online Estimation ◽

Innovative Research ◽

Multiple Neural Networks

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Online estimation of impurity ion concentration in solution purification process**This research was support by Innovation-driven Plan in Central South University (Grant No. 2015cx007), Science Fund for Innovative Research Groups of the National Natural Science Foundation of China (Grand No: 61321003), National Natural Science Foundation of China (Grand No: 61273187).

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2016.10.117 ◽

2016 ◽

Vol 49 (20) ◽

pp. 178-183 ◽

Cited By ~ 2

Author(s):

Bei Sun ◽

Weihua Gui ◽

Chunhua Yang ◽

Yalin Wang ◽

Mingfang He

Keyword(s):

Natural Science ◽

Ion Concentration ◽

Purification Process ◽

Research Groups ◽

Online Estimation ◽

Innovative Research ◽

Impurity Ion ◽

Central South

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Entropy-based estimation of bubble size distributions in froth flotation using B-spline functions**This work was supported by the National Natural Science Foundation of China (Grant No. 61490702 and No. 61503416), the Innovation-driven Plan in Central South University (Grant No. 2015cx007) and the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 61321003).

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2016.10.103 ◽

2016 ◽

Vol 49 (20) ◽

pp. 96-101 ◽

Cited By ~ 3

Author(s):

Jie Han ◽

Chunhua Yang ◽

Xiaojun Zhou ◽

Weihua Gui

Keyword(s):

Bubble Size ◽

Natural Science ◽

Froth Flotation ◽

Spline Functions ◽

Size Distributions ◽

Research Groups ◽

B Spline ◽

Innovative Research ◽

Central South

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Dynamic Simulation of Planetary Rovers with Terrain Property Mapping * Research supported by National Natural Science Foundation of China (Grant No. 61370033), National Basic Research Program of China (Grant No. 2013CB035502), Foundation for Innovative Research Groups of the Natural Science Foundation of China (Grant No. 51521003), Foundation of Chinese State Key Laboratory of Robotics and Systems (Grant No. SKLRS201501B, SKLRS20164B), Harbin Applied Technology Project of Research and Development (2015RQQXJ081), and the “111 Project” (Grant No. B07018).

2018 IEEE International Conference on Robotics and Automation (ICRA) ◽

10.1109/icra.2018.8460755 ◽

2018 ◽

Cited By ~ 1

Author(s):

Huaiguang Yang ◽

Liang Ding ◽

Haibo Gao ◽

Lan Huang ◽

Junlong Guo ◽

...

Keyword(s):

Research And Development ◽

Dynamic Simulation ◽

Research Program ◽

Natural Science ◽

Basic Research ◽

Research Groups ◽

Planetary Rovers ◽

Technology Project ◽

Innovative Research ◽

Applied Technology

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Synchronization of bidirection multiple neural networks with impulsive coupling control

Advances in Difference Equations ◽

10.1186/s13662-020-02796-6 ◽

2020 ◽

Vol 2020 (1) ◽

Author(s):

Yong Wang ◽

Ailong Wu ◽

Biwen Li

Keyword(s):

Neural Networks ◽

Multiple Neural Networks

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Robust classification of multispectral data using multiple neural networks and fuzzy integral

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/36.582004 ◽

1997 ◽

Vol 35 (3) ◽

pp. 787-790 ◽

Cited By ~ 35

Author(s):

A.S. Kumar ◽

S.K. Basu ◽

K.L. Majumdar

Keyword(s):

Neural Networks ◽

Fuzzy Integral ◽

Robust Classification ◽

Multispectral Data ◽

Multiple Neural Networks

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Synchronisation of multiple neural networks via event‐triggered time‐varying delay hybrid impulsive control

IET Control Theory and Applications ◽

10.1049/cth2.12194 ◽

2021 ◽

Author(s):

Xiaoli Ruan ◽

Chen Xu ◽

Jianwen Feng ◽

Jingyi Wang ◽

Yi Zhao

Keyword(s):

Neural Networks ◽

Impulsive Control ◽

Time Varying ◽

Time Varying Delay ◽

Multiple Neural Networks ◽

Varying Delay ◽

Event Triggered

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Image Classification Using Fusion of Multiple Neural Networks

2021 36th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) ◽

10.1109/itc-cscc52171.2021.9501468 ◽

2021 ◽

Author(s):

Jiayi Fan ◽

JangHyeon Lee ◽

YongKeun Lee

Keyword(s):

Neural Networks ◽

Image Classification ◽

Multiple Neural Networks

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Combining multiple neural networks by fuzzy integral for robust classification

IEEE Transactions on Systems Man and Cybernetics ◽

10.1109/21.364825 ◽

1995 ◽

Vol 25 (2) ◽

pp. 380-384 ◽

Cited By ~ 210

Author(s):

Sung-Bae Cho ◽

J.H. Kim

Keyword(s):

Neural Networks ◽

Fuzzy Integral ◽

Robust Classification ◽

Multiple Neural Networks

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Error correction method based on multiple neural networks for UHF partial discharge localization

IEEE Transactions on Dielectrics and Electrical Insulation ◽

10.1109/tdei.2017.006764 ◽

2017 ◽

Vol 24 (6) ◽

pp. 3730-3738 ◽

Cited By ~ 4

Author(s):

Nan Zhou ◽

Lingen Luo ◽

Jingde Chen ◽

Gehao Sheng ◽

Xiuchen Jiang

Keyword(s):

Neural Networks ◽

Error Correction ◽

Partial Discharge ◽

Correction Method ◽

Error Correction Method ◽

Multiple Neural Networks

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Finite-time synchronization of Heterogeneous Fractional-order Multiple Neural Networks with Impulsive Disturbance Via Hybrid Control

10.1109/iccia52886.2021.00028 ◽

2021 ◽

Author(s):

Taotao Hu ◽

Zheng He ◽

Xiaojun Zhang ◽

Shouming Zhong

Keyword(s):

Neural Networks ◽

Fractional Order ◽

Finite Time ◽

Time Synchronization ◽

Hybrid Control ◽

Multiple Neural Networks

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