| Cite this article: | 徐睿,张晓斌,薛鹏松.基于改进的GRNN—Markov水质预测模型研究及应用[J].灌溉排水学报,0,():-. |
| XU Rui,ZHANG Xiaobin,XUE Pengsong.基于改进的GRNN—Markov水质预测模型研究及应用[J].灌溉排水学报,0,():-. |
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| DOI： |
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| Research and application on improved GRNN-Markov water quality prediction model |
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XU Rui1, ZHANG Xiaobin2, XUE Pengsong3
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1.Yuncheng Water Conservancy Survey and Design Research Institute Co., Ltd;2.Yuncheng University;3.Shaanxi Jinke Environmental Protection Engineering Co., Ltd.
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| Abstract: |
| 【Objective】Build an improved GRNN-Markov water quality prediction model, which provides a reliable method for simulating uncertain, complex and variable river water quality trends.【Method】 According to actual situation of water quality in Fen River’s estuary to Yellow River, taking the main pollutant CODcr as the research index, the water quality monitoring data were preprocessed using the Laida criteria. Using Grey Relational Analysis to determine input nodes of GRNN Network which solved the problem that the GRNN network unable to auto select and optimize input nodes. In order to obtain more accurate results and reduce the prediction error of the GRNN network, an improved GRNN-Markov water quality prediction model was constructed to improve the water quality prediction accuracy.【Result】The combined model provides new ideas and methods for water environmental protection and governance.The research show that the improved GRNN-Markov water quality prediction model can improve the accuracy of water quality prediction results. Relative error was-38.27% ~ -15.71% based on GRA—GRNN model, Relative error was-25.77% ~ -5.25% based on improved GRNN-Markov water quality prediction model, the correction result was close to the measured value.【Conclusion】This combination model can be used in water quality prediction based on small sample data. This study provides a scientific basis for water environment management. |
| Key words: grey relational analysis (GRA); improved GRNN-Markov model; Fen River’s estuary to Yellow River; water quality prediction |
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