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| Robust SoftSensing of Slurry pH Using LSSVR for Mineral Flotation Process |
| REN Hui-Feng, YANG Chun-Hua, ZHOU Xuan, GUI Wei-Hua, YAN Feng |
| (School of Information Science and Engineering, Central South University, Changsha 410083, China) |
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Abstract Considering the poor stability of detectors and serious manual detection timedelay, a novel soft sensor was proposed based on least squares support vector regression (LSSVR) with sparsity using image features as instrumental variable. Firstly, multiple kernels were combined and the kernel matrix was reduced according to an improved minus cluster algorithm. Then the partial least squares regression was used to improve the robustness and precision of the soft sensor. The experiment verified the presented model which performs high precision and good reliability compared with standard LSSVR, weighted LSSVR and multiplekernel LSSVR.
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Received: 22 April 2011
Published: 30 August 2011
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