Modelling algal blooms in Lake Dianchi, China using neural networks
文献类型：期刊论文
| 作者 | Li, Hongbin; Hou, Guoxiang; Song, Lirong; Liu, Yongding |
| 刊名 | FRESENIUS ENVIRONMENTAL BULLETIN
 |
| 出版日期 | 2007 |
| 卷号 | 16期号:7页码:798-803 |
| 关键词 | algal dynamics algal bloom neural network pH sensitivity analysis |
| ISSN号 | 1018-4619 |
| 通讯作者 | Hou, GX, Huazhong Univ Sci & Technol, Dept Ocean Sci & Engn, 1037 Luoyu Rd, Wuhan 430074, Peoples R China |
| 中文摘要 | Lake Dianchi is one of the most extensively impacted freshwater lakes by algal blooms. To investigate the response of dominant algal genera, neural networks were applied to model the relationship between water quality parameters and the biomass of four dominant genera (Microcystic spp., Anabaena sp., Quadricauda (Turp.) Breb, Pediastrum Mey) in Dianchi. Results showed that the timing and magnitude of algal blooms of Microcystic spp., nabaena sp., Quadricauda (Turp.) Breb, and Pediastrum Mey in Dianchi could be successfully predicted. The evaluation of environmental factors showed that pH had more significant impact on concentrations of all the four dominant algal genera than the nutrient factors, such as total phosphorus and total nitrogen. |
| 英文摘要 | Lake Dianchi is one of the most extensively impacted freshwater lakes by algal blooms. To investigate the response of dominant algal genera, neural networks were applied to model the relationship between water quality parameters and the biomass of four dominant genera (Microcystic spp., Anabaena sp., Quadricauda (Turp.) Breb, Pediastrum Mey) in Dianchi. Results showed that the timing and magnitude of algal blooms of Microcystic spp., nabaena sp., Quadricauda (Turp.) Breb, and Pediastrum Mey in Dianchi could be successfully predicted. The evaluation of environmental factors showed that pH had more significant impact on concentrations of all the four dominant algal genera than the nutrient factors, such as total phosphorus and total nitrogen. |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine |
| 学科主题 | Environmental Sciences |
| 类目[WOS] | Environmental Sciences |
| 研究领域[WOS] | Environmental Sciences & Ecology |
| 关键词[WOS] | CROSS-VALIDATION |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000248571800014 |
| 公开日期 | 2010-10-13 |
| 源URL | [http://ir.ihb.ac.cn/handle/152342/8492]  |
| 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 | 1.Huazhong Univ Sci & Technol, Dept Ocean Sci & Engn, Wuhan 430074, Peoples R China 2.Chinese Acad Sci, Inst Hydrobiol, Wuhan 430072, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Hongbin,Hou, Guoxiang,Song, Lirong,et al. Modelling algal blooms in Lake Dianchi, China using neural networks[J]. FRESENIUS ENVIRONMENTAL BULLETIN,2007,16(7):798-803. |
| APA | Li, Hongbin,Hou, Guoxiang,Song, Lirong,&Liu, Yongding.(2007).Modelling algal blooms in Lake Dianchi, China using neural networks.FRESENIUS ENVIRONMENTAL BULLETIN,16(7),798-803. |
| MLA | Li, Hongbin,et al."Modelling algal blooms in Lake Dianchi, China using neural networks".FRESENIUS ENVIRONMENTAL BULLETIN 16.7(2007):798-803. |
入库方式： OAI收割
来源：水生生物研究所
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