凡纳滨对虾养殖水质预警研究
赵建文
【期刊名称】《计算机仿真》 【年(卷),期】2013(030)001
【摘要】Research accurate warning of prawn breeding water quality. The dynamic change of water quality is complex. This paper put forward a T-S fuzzy neural network water quality monitoring model. This method combines the fuzzy system reasoning ability and network self— learning ability to identify the structure and parameters of water quality system. All kinds of corresponding laws between water quality factors and ranks were establishing. The experiment results show that the algorithm improves the accuracy of identification.%研究对虾养殖水质准确预警问题.对虾的活动性极低,对水质的动态变化影响的周期很长,使得对虾养殖水质因子的突变性很小,使得对虾养殖中的水质因子存在非线性、不确定、难以精确评价的难点.传统的水质监测方法多是基于水质瞬间突变,根据水质因子的瞬间异常变化作出报警.如果水质因子的突变性较小,将很难作出及时准确的监测,不能做出及时预警.提出了一种T-S模糊神经网络的水质监测建模方法.该方法结合了模糊系统的推理能力和网络的自学习能力,通过对水质标准模糊系统的结构辨识和参数辨识,建立各种水质因子和水质等级之间的非线性对应规律.实验证明该方法很好的解决了对虾养殖中的水质监测问题. 【总页数】4页(373-376)
【关键词】模糊神经网络;凡纳滨对虾;水质评价
凡纳滨对虾养殖水质预警研究
