摘要
本文将计算机人工神经网络理论首次引入灌溉宏观发展战略研究领域，以各“五年”计划期末全国粮食总产与影响因子集为训练样本，建立了灌溉发展需求预测人工神经网络模型；从建国以来４０多年的时间序列中，任选５个年份的相应参数作为校核样本，对所建模型进行了校核；根据今后我国人口增长与粮食需求发展趋势，利用模型对未来３０年全国的灌溉面积发展需求进行了预测；分析了预测结果，提出了发展对策．其成果对制定全国灌溉宏观发展战略与政策措施，确保未来３０年中国粮食与经济安全具有十分重要的参考意义．
In this paper,neural network theory has been introduced to predict Irrigation needs in the following 30 years in China. Using the gross product of grain food at the end year of each “five year” period and its affecting data,a neural network model for irrgation needs predicting has been established. According to the change tend of national population and food need,the required national effective irrigation area by the year 2000,2010,2020 and 2030 have been predicted.The main obstacles resisting irrigation sector development has been diagnosed,and development strategies has been suggested,which is seting up market irrigtion operation system;strenthening government policy ajustment and control; developing water saving irrigation technology.
出处
《水利学报》
EI
CSCD
北大核心
1998年第2期1-6,共6页
Journal of Hydraulic Engineering
关键词
灌溉
人工神经网络
预测
粮食
计算机应用
Irrigation,Neural Network,Prediction,Food grain,Development Needs,Computer
