In this paper,the artificial lake on the campus of Tibet University was taken as the research object.By detecting the water quality of the lake,the standard index method and comprehensive pollution index method were u...In this paper,the artificial lake on the campus of Tibet University was taken as the research object.By detecting the water quality of the lake,the standard index method and comprehensive pollution index method were used to understand the water quality characteristics,pollution status,and main pollutants of the Siyuan Lake.On this basis,the comprehensive nutritional status index method was used to evaluate the eutrophication status of the Siyuan Lake.The results showed that the overall water quality of the artificial lake was good,showing as still clean,with TN and TP being the main pollution factors of the artificial lake.The main nutritional indicators were TN,TP,and transparency,with a comprehensive nutritional level of middle eutropher.Based on the environmental characteristics of the artificial lake area on the campus of Tibet University,reasonable treatment measures have been proposed.It hoped to prevent and improve the water environment through these measures,and provide reference for the protection and restoration of campus landscape water body.展开更多
An adaptive neuro fuzzy inference system was used for classifying water quality status of river. It applied several physical and inorganic chemical indicators including dissolved oxygen, chemical oxygen demand, and am...An adaptive neuro fuzzy inference system was used for classifying water quality status of river. It applied several physical and inorganic chemical indicators including dissolved oxygen, chemical oxygen demand, and ammonia-nitrogen. A data set （nine weeks, total 845 observations） was collected from 100 monitoring stations in all major river basins in China and used for training and validating the model. Up to 89.59% of the data could be correctly classified using this model. Such performance was more competitive when compared with artificial neural networks. It is applicable in evaluation and classification of water quality status.展开更多
基金Supported by Innovative Projects for University Students(2022XCX020).
文摘In this paper,the artificial lake on the campus of Tibet University was taken as the research object.By detecting the water quality of the lake,the standard index method and comprehensive pollution index method were used to understand the water quality characteristics,pollution status,and main pollutants of the Siyuan Lake.On this basis,the comprehensive nutritional status index method was used to evaluate the eutrophication status of the Siyuan Lake.The results showed that the overall water quality of the artificial lake was good,showing as still clean,with TN and TP being the main pollution factors of the artificial lake.The main nutritional indicators were TN,TP,and transparency,with a comprehensive nutritional level of middle eutropher.Based on the environmental characteristics of the artificial lake area on the campus of Tibet University,reasonable treatment measures have been proposed.It hoped to prevent and improve the water environment through these measures,and provide reference for the protection and restoration of campus landscape water body.
基金supported by the National Natural Science Foundation of China(No. 50778009)
文摘An adaptive neuro fuzzy inference system was used for classifying water quality status of river. It applied several physical and inorganic chemical indicators including dissolved oxygen, chemical oxygen demand, and ammonia-nitrogen. A data set （nine weeks, total 845 observations） was collected from 100 monitoring stations in all major river basins in China and used for training and validating the model. Up to 89.59% of the data could be correctly classified using this model. Such performance was more competitive when compared with artificial neural networks. It is applicable in evaluation and classification of water quality status.
