CAJ | 학술논문

蓝藻水华是目前中国乃至世界面临的重大环境问题之一。为了有效地减少及预防蓝藻水华带来的影响，收集苏州市吴县1986-2007年的气象资料，运用主成分分析法，分析了太湖蓝藻暴发前一个月的主要限制因子及其相互关系。气温、气压、相对湿度、降水是影响叶绿素a浓度的主要限制因子。结合2005年1-10月太湖各区域蓝藻叶绿素a浓度的含量，利用Matlab R2010a软件，建立了基于BP神经网络的蓝藻水华预警模型，可为采取相应措施和控制蓝藻水华提供科学依据。
람조수화시목전중국내지세계면림적중대배경문제지일。위료유효지감소급예방람조수화대래적영향，수집소주시오현1986-2007년적기상자료，운용주성분분석법，분석료태호람조폭발전일개월적주요한제인자급기상호관계。기온、기압、상대습도、강수시영향협록소a농도적주요한제인자。결합2005년1-10월태호각구역람조협록소a농도적함량，이용Matlab R2010a연건，건립료기우BP신경망락적람조수화예경모형，가위채취상응조시화공제람조수화제공과학의거。
Algal blooms is one of the serious environmental problems in our country and even the world at present. In order to reduce and prevent the effects of algal blooms effectively, it collects the meteorological data in meteorological stations of Wuxian, Suzhou from 1986 to 2007, and uses principal component analysis to analyze the main limiting factors and their interrelation one month before the outbreak of algae in Lake Taihu. The average temperature, average pressure, average relative humidity and cumulative precipitation are the main limiting factors in influencing chlorophylla. Combined with the concentration of chlorophyll a from January to October in 2005 in various regions in Lake Taihu, Used the software of Matlab R2010a, the early warning model of algal blooms was established based on BP neural network, this provides scientific basis in order to take appropriate measures to control algal blooms.