文章摘要
刘明,李由明,王平,李晓梅.基于小波分解的凡纳滨对虾养殖水体水质的仿真研究[J].广东农业科学,2013,40(17):170-172
查看全文    HTML 基于小波分解的凡纳滨对虾养殖水体水质的仿真研究
Phantom study on water quality dynamic in Litopenaeus vannameiis's ponds based on wavelet analysis
  
DOI:
中文关键词: 小波分解  ARMA 模型  神经网络模型  凡纳滨对虾  亚硝酸盐
英文关键词: ARMA Model  Neural Network Model  Litopenaeus vannameiis  nitrites
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作者单位
刘明,李由明,王平,李晓梅 1.琼州学院电子信息工程学院海南三亚5720222.琼州学院生物科学与技术学院海南三亚5720223.海南南疆生物技术有限公司海南昌江572700 
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中文摘要:
      依据凡纳滨对虾养殖水体中测定的水质数据,利用ARMA 模型和神经网络模型两种方法对水质动态进行预测和分 析,提出了一种基于小波分解且针对凡纳滨对虾养殖水体水质预测的ARMA 模型,且ARMA(p,q)模型中的p 值和q 值分别为4和2。预测结果表明,所建立的预测模型精度较高。将ARMA 模型预测的结果与神经网络预测的结果进行了对比后发现,基于小波分解的ARMA 模型对对虾养殖水体水质预测的有效性和准确性优于神经网络预测模型。
英文摘要:
      Dynamics of water quality was predicted by ARMA Models and Neural Network Models in this paper. A ARMA Model for water quality of Litopenaeus vannameiis's ponds has been raised based on data from shrimps ponds,and the values of p and q of ARMA(p, q) were 4 and 2 respectively. Results of prediction indicated that accuracy of ARMA Model was high. Moreover, comparison of effectivity and accuracy between ARMA Model and Neural Network Models indicated that the former was better for prediction of water quality of shrimp ponds.
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