Int. J. of Wireless and Mobile Computing   »   2014 Vol.7, No.2

 

 

Title: Three-dimensional fluorescence spectra model optimisation for water quality analysis based on particle swarm optimisation

 

Authors: Xiao-Li Wu; Jin-Rong Li; Jing Jie; Hui Zheng

 

Addresses:
School of Automation and Electrical Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China
School of Automation and Electrical Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China
School of Automation and Electrical Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China
School of Automation and Electrical Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China

 

Abstract: In this paper, a model combination method is proposed to improve the model precision of water quality analysis with three-dimensional (3D) fluorescence spectra. The key to successful model combination is the selection of sub-models, which also means selection of excitation wavelength for 3D fluorescence instrument miniaturisation. A particle swarm optimisation (PSO) algorithm is designed to select effective sub-models, in which the combinational model is built. Field samples from surface water and urban wastewater are used as research objects. Following the proposed PSO method, three excitation wavelengths were selected, and the corresponding sub-models were linearly combined to an optimised combinational model. The experimental results showed that the root mean square errors of prediction of the combinational model decreased significantly, whether compared with the sub-models having the best prediction precision or the combinational models without sub-models selection.

 

Keywords: PSO; particle swarm optimisation; water quality analysis; 3D fluorescence spectra; model combination; excitation wavelength selection; sub-model selection; surface water; urban wastewater; modelling; combinational models.

 

DOI: 10.1504/IJWMC.2014.059718

 

Int. J. of Wireless and Mobile Computing, 2014 Vol.7, No.2, pp.200 - 206

 

Submission date: 23 May 2013
Date of acceptance: 31 Aug 2013
Available online: 07 Mar 2014

 

 

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