水土保持通报2012，Vol.32Issue(1)：189-191,232,4.
象山港海水养殖区贝叶斯网络水质评价及预测
Assessment and Prediction of Water Quality in Mariculture Zone of Xiangshan Harbor Based on Bayesian Network
滕丽华 1程利江 1王海丽 1杨季芳1
作者信息
- 1. 浙江万里学院生物与环境学院,浙江宁波315100
- 折叠
摘要
Abstract
Water quality assessment plays an important role in water environmental protection and management.Traditional methods have some limitations in dealing with the uncertainty in assessment and massive information.A Bayesian network model can effectively express and analyze uncertain problems and combine qualitative analysis with quantitative analysis.Based on the mornitoring data for nearly ten years in Xiang-shan harbor of Ningbo City,a Bayesian network model expressing the relationships and interactions between different water quality indexes and water quality levels was constructed by Bayesian network approach.The model structure indicated that ammonia nitrogen,COD,inorganic phosphorus,nitrate,and chlorophyll had direct effects on water quality level,whereas there was an indirect causality between other water quality indexes such as nitrite and inorganic nitrogen and water quality level.The results of the model validation using 200 monitoring data showed that the predictive precision reached 94.8% and the Kappa was 0.892,which suggests the Bayesian network is feasible for assessment and prediction of water quality.关键词
水质/评价/贝叶斯网络Key words
water quality/assessment/Bayesian network分类
资源环境引用本文复制引用
滕丽华,程利江,王海丽,杨季芳..象山港海水养殖区贝叶斯网络水质评价及预测[J].水土保持通报,2012,32(1):189-191,232,4.
