广东化工
廣東化工
엄동화공
GUANGDONG CHEMICAL INDUSTRY
2012年
10期
68-69
,共2页
BP神经网络模型%集雨窖水%水质综合评价
BP神經網絡模型%集雨窖水%水質綜閤評價
BP신경망락모형%집우교수%수질종합평개
BP neural network model%rainwater collection%comprehensive assessment of water quality
本研究以会宁地区集雨窖水水质中的CODMn、NH3-N、DO三个参评指标作为集雨窖水水质等级评价的输入特征值，建立了BP神经网络水质评价模型，得出集雨初期的窖水水质基本上为v类或超v类，随着时间的增长窖水水质有明显改善，可达到I～Ⅱ类水质。
本研究以會寧地區集雨窖水水質中的CODMn、NH3-N、DO三箇參評指標作為集雨窖水水質等級評價的輸入特徵值，建立瞭BP神經網絡水質評價模型，得齣集雨初期的窖水水質基本上為v類或超v類，隨著時間的增長窖水水質有明顯改善，可達到I～Ⅱ類水質。
본연구이회저지구집우교수수질중적CODMn、NH3-N、DO삼개삼평지표작위집우교수수질등급평개적수입특정치，건립료BP신경망락수질평개모형，득출집우초기적교수수질기본상위v류혹초v류，수착시간적증장교수수질유명현개선，가체도I～Ⅱ류수질。
The study was to establish BP neural network models, in which CODMn, NH3-N, DO in were used as the reference index for comprehensive assessment of water quality of harvested rainwater in northwest china, the harvested rainwater of huining area. The quality of initial harvested rainwater in water cellars were class V or much higher than water quality standard, but the water quality was ameliorate from inferior standard V to standard I or Ⅱ with time prolong.
