Environmental & Analytical Toxicology

Dan Yu

Publications

• Research Article
  GA-SVM Applied in Assessing the Water Trophic State of South Lake Qujiang based on Multispectral RS
  Author(s): Aidi Huo, Xiaolu Zheng, Guoliang Wang, Juan Xie, Dan Yu, Hong Wei and Xiaofan WangAidi Huo, Xiaolu Zheng, Guoliang Wang, Juan Xie, Dan Yu, Hong Wei and Xiaofan Wang
  
  Eutrophication has become a major water quality problem in most urban landscape waters of the world. Despite extensive research over the last four to five decades, many of the key issues in eutrophication science remain unsolved. In this paper, based on Support Vector Machine (SVM) a new method was proposed to monitor and evaluate the water trophic state of Qujiang South Lake. SVM is suitable for a limited number of samples because of strong nonlinear mapping ability. Model parameters can be automatically chosen by Genetic Algorithm (GA) which contributes to advantages of the Genetic Algorithm- Support Vector Machine (GA-SVM) which has high precision in solving regression problems. Enhanced Thematic Mapper (ETM) data can be used to estimate the chlorophyll-a (Chl-a) concentration of the water body. The characteristic band ratio and SVM method are used to establish a model of Chl-a con.. Read More»
  DOI: 10.4172/2161-0525.1000494

  Abstract PDF