A new approach to coastal water quality assessment was put forward through study on self-organizing map （ SOM ）. Firstly, the water quality data of Bohai Bay from 1999 to 2002 were prepared. Then, a set of software ...A new approach to coastal water quality assessment was put forward through study on self-organizing map （ SOM ）. Firstly, the water quality data of Bohai Bay from 1999 to 2002 were prepared. Then, a set of software for coastal water quality assessment was developed based on the batch version algorithm of SOM and SOM toolbox in MATLAB environment. Furthermore. the training results of SOM could be analyzed with single water quality indexes, the value of N ： PC atomic ratio） and the eutrophication index E so that the data were clustered into five different pollution types using k-means clustering method. Finally, it was realized that the monitoring data serial trajectory could be tracked and the new data be classified and assessed automatically. Through application it is found that this study helps to analyze and assess the coastal water quality by several kinds of graphics, which offers an easy decision support for recognizing pollution status and taking corresponding measures.展开更多
基金Supported by Tianjin Municipal Science and Technology Commission ( No. 033113811) and Young Teacher Foundation of Tianjin University ( No. 985200540).
文摘A new approach to coastal water quality assessment was put forward through study on self-organizing map （ SOM ）. Firstly, the water quality data of Bohai Bay from 1999 to 2002 were prepared. Then, a set of software for coastal water quality assessment was developed based on the batch version algorithm of SOM and SOM toolbox in MATLAB environment. Furthermore. the training results of SOM could be analyzed with single water quality indexes, the value of N ： PC atomic ratio） and the eutrophication index E so that the data were clustered into five different pollution types using k-means clustering method. Finally, it was realized that the monitoring data serial trajectory could be tracked and the new data be classified and assessed automatically. Through application it is found that this study helps to analyze and assess the coastal water quality by several kinds of graphics, which offers an easy decision support for recognizing pollution status and taking corresponding measures.
