Guangzhou Water Research Institute

Guangzhou, China

Guangzhou Water Research Institute

Guangzhou, China
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Xiao T.,Hunan University | Yuan X.,Hunan University | Tang Q.,Guangzhou Water Research Institute | Gao Q.,Guangzhou Water Research Institute | And 8 more authors.
Huanjing Kexue Xuebao/Acta Scientiae Circumstantiae | Year: 2013

As one kind of artificial neural networks, probabilistic neural networks (PNN) is simple in structure, easy for training and widely used. Some research results have been obtained in environmental area, for example the classification of water quality. The target of this study was Baiyun Lake, the biggest artificial lake of Guangzhou city. Based on the monitoring data of water quality and biology, PNN model was constructed and applied to assess the ecosystem of Baiyun Lake at different periods. The main assessment results are listed as follows: (1) the ecological system of Baiyun Lake was relatively weak, which was unable to function in purifying water. (2) The seasonal variation of health assessment results at different monitoring points was significant, while the inter-annual variation was insignificant.In summary, it is feasible to assess the health of the lake ecosystem by probabilistic neural network. Compared with traditional evaluation methods, e.g. BP neural networks and attribute recognition method, the PNN model is more objective and stable in evaluating the health of lake ecosystem, thus can be extended to other related fields.


Bi W.,Hunan University | Yuan X.,Hunan University | Tang Q.,Guangzhou Water Research Institute | Gao Q.,Guangzhou Water Research Institute | And 5 more authors.
Huanjing Kexue Xuebao/Acta Scientiae Circumstantiae | Year: 2012

A health assessment model for lake ecosystem was proposed based on the strengths of support vector machine (SVM) on dealing with classification, small sample size, generalization and promotion. Meanwhile, a survey was conducted on the water quality and biological communities of Baiyun Lake, the largest artificial lake in Guangzhou city. Afterwards, the health assessment of Baiyun Lake ecosystem was evaluated with this model. It was demonstrated by the assessment results that the ecosystem of Baiyun Lake was in pathological state, and unable to function in purifying water. To improve the ecological system of Baiyun Lake, three methods were suggested including improving input water quality, cutting pollution sources and enriching biomass. Compared with two traditional evaluation methods (Entropy weight comprehensive health index method and Entropy weight fuzzy comprehensive evaluation method), this model is more objective and scientific on evaluating the health of lake ecosystem. It can provide scientific support for health management of lake ecosystem, therefore with a promising application prospect.


Tang Q.,Guangzhou Water Research Institute | Gao Q.,Guangzhou Water Research Institute | Pang Z.,Guangzhou Water Research Institute | Bi W.,Hunan University | And 4 more authors.
Chinese Journal of Environmental Engineering | Year: 2014

Baiyun Lake is the largest artificial ecosystem lake in Guangzhou city. Through designing the ecological remediation in Baiyun Lake, a series of new environmental technologies were adopted, including carbon fiber eco-grass, micro-nano bubble generating device, pure oxygen generator, solar dynamic water algae removal machine and ecological floating bed combining manual intervention and biological treatment, together with constructed wetland and ecological embankment technologies. Meanwhile, water quality of the lake was tracked and monitored. The results show that the water quality of Baiyun Lake has been distinctly improved after the implementation of the water quality promotion projectin Baiyun Lake. The design experience of the ecological remediation in Baiyun Lake will provide reference value for an analogous project such as the improvement of water quality and the ecological remediation of artificial water bodies.


Chen Y.,Hunan University | Zhu G.,Hunan University | Tang Q.,Guangzhou Water Research Institute | Gao Q.,Guangzhou Water Research Institute | And 2 more authors.
Chinese Journal of Environmental Engineering | Year: 2014

Support vector machine (SVM) is easy to be spread and generalized and has an advantage in dealing with classification and small sample size problems. An evaluation model of lake water quality was proposed based on SVM and was used to evaluate the water quality of Baiyun Lake in Guangzhou. The water quality in the intake (A), outlet (E) and central area (B, C, and D) of Baiyun Lake was monitored three times in 2011, respectively. The analysis results showed that the water qualities of Baiyun Lake except site B (class IV) were belonging to class V in January. In April, except site A (class V), the remaining sites were all classified as grade IV. In August, the water quality of site A was transferred to class IV and the other sites were improved to class II. After the unstable state, Baiyun Lake is gradually achieving the design goal of water purification. Compared with the results evaluated by other common methods, these results were more scientific and reasonable. ©, 2014, Science Press. All right reserved.

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