Modeling of cyanobacterial blooms in hypereutrophic Lake Dianchi, China
文献类型：期刊论文
| 作者 | Hou, GX; Song, LR; Liu, JT; Xiao, BD; Liu, YD |
| 刊名 | JOURNAL OF FRESHWATER ECOLOGY
 |
| 出版日期 | 2004-12-01 |
| 卷号 | 19期号:4页码:623-629 |
| 关键词 | NEURAL NETWORKS |
| ISSN号 | 0270-5060 |
| 通讯作者 | Liu, YD, Chinese Acad Sci, Inst Hydrol, State Key Lab Freshwater Ecol & Biotechnol, Wuhan 430072, Peoples R China |
| 中文摘要 | Compared with other approaches for modeling and predicting, artificial neural networks are more effective in describing complex and non-linear systems. The occurrence of cyanobacterial blooms has been a continuous and serious problem over the past decades in hypereutrophic Lake Dianchi. Yet, the main factor(s) initiating these blooms remain(s) unclear. During 2001-2002 at 40 sampling sites in Lake Dianchi, physicochemical parameters possibly relating to the blooms were measured. Parameters directly or indirectly relating to the cyanobacterial blooms were used as driving factors in a back-propagation network to model the concentration of chlorophyll a. According to sensitivity analysis, chemical oxygen demand was identified as a very significant environmental factor for algal growth in Lake Dianchi. |
| 英文摘要 | Compared with other approaches for modeling and predicting, artificial neural networks are more effective in describing complex and non-linear systems. The occurrence of cyanobacterial blooms has been a continuous and serious problem over the past decades in hypereutrophic Lake Dianchi. Yet, the main factor(s) initiating these blooms remain(s) unclear. During 2001-2002 at 40 sampling sites in Lake Dianchi, physicochemical parameters possibly relating to the blooms were measured. Parameters directly or indirectly relating to the cyanobacterial blooms were used as driving factors in a back-propagation network to model the concentration of chlorophyll a. According to sensitivity analysis, chemical oxygen demand was identified as a very significant environmental factor for algal growth in Lake Dianchi. |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine |
| 学科主题 | Ecology; Limnology |
| 类目[WOS] | Ecology ; Limnology |
| 研究领域[WOS] | Environmental Sciences & Ecology ; Marine & Freshwater Biology |
| 关键词[WOS] | NEURAL NETWORKS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000225656300013 |
| 公开日期 | 2010-10-13 |
| 源URL | [http://ir.ihb.ac.cn/handle/152342/9360]  |
| 专题 | 水生生物研究所_中科院水生所知识产出（2009年前）_期刊论文 |
| 作者单位 | Chinese Acad Sci, Inst Hydrol, State Key Lab Freshwater Ecol & Biotechnol, Wuhan 430072, Peoples R China |
| 推荐引用方式 GB/T 7714 | Hou, GX,Song, LR,Liu, JT,et al. Modeling of cyanobacterial blooms in hypereutrophic Lake Dianchi, China[J]. JOURNAL OF FRESHWATER ECOLOGY,2004,19(4):623-629. |
| APA | Hou, GX,Song, LR,Liu, JT,Xiao, BD,&Liu, YD.(2004).Modeling of cyanobacterial blooms in hypereutrophic Lake Dianchi, China.JOURNAL OF FRESHWATER ECOLOGY,19(4),623-629. |
| MLA | Hou, GX,et al."Modeling of cyanobacterial blooms in hypereutrophic Lake Dianchi, China".JOURNAL OF FRESHWATER ECOLOGY 19.4(2004):623-629. |
入库方式： OAI收割
来源：水生生物研究所
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