基于灰色系统理论的网箱养殖大黄鱼Pseudosciaena crocea (Richardson)疾病预报
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宁波大学,宁波大学海洋学院,宁波大学海洋学院,宁波市海洋渔业研究院

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A forecasting model for bacteroidal disease of cage cultured large yellow croaker (Pseudosciaena crocea) based on grey system theory
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School of Marine Sciences,Ningbo Unversity,School of Marine Sciences,Ningbo Unversity,School of Marine Sciences,Ningbo Unversity,Ningbo Marine Fisheries Research Institute

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    摘要:

    为预报网箱养殖大黄鱼细菌性疾病的发生,以舟山市网箱养殖大黄鱼为研究对象,应用灰色系统理论探索了网箱养殖大黄鱼细菌性疾病的发生发展规律及其与环境因子的关系;建立了灰色(GM)预报模型,预报网箱养殖大黄鱼细菌性疾病的发生时间和发病率。灰色关联分析结果表明大黄鱼细菌性疾病的发病率与养殖水域的环境因子都有不同程度的关联,把水温、悬浮物、无机氮和COD选作先行指标,用这些因子的不同组合建立了GM(1,5)、GM(1,4)和GM(1,3)模型,比较这些模型的平均相对误差,由无机氮和COD构成的GM(1,3)模型平均相对误差最小,为5.304%。用GM(1,1)模型对大规模细菌性疾病发生的时间进行了预测,预测的准确率达到90.5%。

    Abstract:

    Based on the grey system theory, the occurring rule of the bacteroidal disease of cage cultured large yellow croaker (Pseudosciaena crocea) in Zhoushan was examined, and the relationship between the disease and environmental factors of surrounding sea waters was investigated. The grey models were established for forecasting the relevant data or incidence of the disease. The grey incidence analysis showed that the incidence of the disease was related to environmental factors in the different extent. Taking water temperature, the suspended solid, inorganic nitrogen and COD as forecasting factors, the GM(1,5), GM(1,4) and GM(1,3) were constructed respectively. Compared these models, the GM(1,3) constructed by inorganic nitrogen and COD had least mean relative simulation error. GM(1,1) was also established for the forecasting of the occurring data of the bacteroidal disease in wider scope, its veracity reached up to 90.5%.

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倪海儿,Owen Mbokigwe Kibona,王国良,吴云飞.基于灰色系统理论的网箱养殖大黄鱼Pseudosciaena crocea (Richardson)疾病预报[J].水产学报,2013,37(6):920~926

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  • 收稿日期:2012-11-13
  • 最后修改日期:2013-04-16
  • 录用日期:2013-05-19
  • 在线发布日期: 2013-06-18
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