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人工神经网络预报浮游植物生长趋势的研究
引用本文:吴京洪,杨秀环,唐宝英,张展霞,李锦蓉. 人工神经网络预报浮游植物生长趋势的研究[J]. 中山大学学报(自然科学版), 2000, 39(6): 54-58
作者姓名:吴京洪  杨秀环  唐宝英  张展霞  李锦蓉
作者单位:1. 中山大学化学与化学工程学院,广东广州 510275
2. 中山大学化学与化学工程学院,广东广州 510275;
3. 国家海洋局南海监测中心,广东广州 510300
基金项目:国家自然科学基金重大项目资助(3979011003)
摘    要:提出用人工神经网络预报赤潮多发海区浮游植物生长趋势,并以1998年4~5月大亚湾澳头港实际监测数据为对象,以采样深度、水温、盐度、pH、DO、COD、浊度、营养盐、叶绿素a、微量元素、总碱度、气温、气压、风速、风向、光照、潮汐、总细胞密度等为参数,试验了工人神经网络的效果。结果表明,人工神经网络可望成为赤潮预报的有效方法。

关 键 词:人工神经网络 赤潮 浮游植物 生长趋势 预报
文章编号:0529-6579(2000)06-0054-05
修稿时间:1999-12-18

The Application of Artificial Neural Network in Forecast of Growth Trends of Phytoplankton
WU Jing|hongSchool of Chemistry and Chemical Engineering,Zhongshan University,Guangzhou ,China,YANG Xiu|huan,TANG Bao|ying,ZHANG Zhan|xia,LIN Jin|rong. The Application of Artificial Neural Network in Forecast of Growth Trends of Phytoplankton[J]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2000, 39(6): 54-58
Authors:WU Jing|hongSchool of Chemistry  Chemical Engineering  Zhongshan University  Guangzhou   China  YANG Xiu|huan  TANG Bao|ying  ZHANG Zhan|xia  LIN Jin|rong
Affiliation:WU Jing|hongSchool of Chemistry and Chemical Engineering,Zhongshan University,Guangzhou 510275,China,YANG Xiu|huan,TANG Bao|ying,ZHANG Zhan|xia,LIN Jin|rong
Abstract:The application of artificial neural network in forecast of growth trends of phytoplankton is suggested.Based on the observing data at Autou Harbour, Daya Bay, from April to May, 1998, the artificial neural network is tested with the environmental factors being taken into consideration, i^e^ sampling depth, water temperature, salinity, pH, DO, COD, turbity, nutrient salt, chloraphyl a, micro inorganic element, total alkalinity, air temperature, air pressure, wind speed, wind direction, illumination, tide, and total cell density.The result shows that the artificial neural network would be an available method in red tide forecast.
Keywords:artificial neural network  phytoplankton  growth trends
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