基于贝叶斯网的网箱养殖区网箱移动预测建模

由专家知识和给定数据,采用著名贝叶斯网络学习K2算法构造了一个海底网箱养殖水环境指标与网箱移动间的贝叶斯网结构模型.该模型能有效的表达网箱养殖环境各个指标之间以及与网箱移动之间的因果关系和影响程度,实验结果表明,试验数据显示准确性为90.6%,以上证明该方法是有效可行的,表明贝叶斯网络是一种很有前途的网箱移动预测评价方法.

The model based on the Bayesian network forecasting the net-cages mobile

A model of the Bayesian network was constructed by K2 algorithm of Bayesian network for the period of net-cages mobile through expert knowledge and the dataset.The model could effectively express the causal relationship and impacts among the indicators in the various cage aquaculture environments.The experimental results based on the test data-set showed that evaluation accuracy was 90.6%.These meant that the method is feasible and efficient.So Bayesian network is a promising approach for the prediction.