Evaluation of environmental factors on cyanobacterial bloom using artificial nueral networks

摘要：

Cyanobacterial blooms are a worldwide issue in eutrophic freshwater. Some cyanobacteria produce toxins, threatening the health of humans and livestock. Microcystin, a representative cyanobacterial hepatotoxin, is frequently detected in most Korean freshwater. This study developed prediction models for cyanobacterial bloom using artificial neural networks (self-organizing map (SOM) and multilayer perceptron (MLP)). Fourteen environmental factors, as independent variables for predicting the cyanobacteria density, were measured weekly in the Daechung Reservoir from spring to autumn over five years (2001, 2003 - 2006).

作者: Chi-Yong Ahn Young-Seuk Park Hee-Mock Oh

作者单位: Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 305-806, Republic of Korea Kyung Hee University, Seoul 130-701, Republic of Korea

会议类型: 国际会议

会议名称: 亚洲微囊藻研究国际学术研讨会

会议地点: 武汉

会议语种:英文

页码: 22

在线出版日期: 2011-04-05（万方平台首次上网日期，不代表论文的发表时间）