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在凡纳滨对虾集约化淡水养殖中,温度、pH值、非离子氨质量浓度是3项重要的水质因子,三者之间存在着非线性耦合关系。基于这一耦合关系,提出水质信息融合Agent结构和二级信息融合算法。在融合算法的第一级,采用正向推理机制,基于规则库推断水质因子是否超标。在融合算法的第二级,根据水质因子的耦合关系模型,采用数据库搜索和固定步长搜索策略寻找合适的温度和pH值,通过在线调节温度和pH值的方法,同时将温度、pH值、非离子氨质量浓度调整至合理范围,以满足养殖要求。试验结果表明,信息融合算法能够有效地调节养殖水质,减少换水次数。
Among the freshwater aquaculture of shrimp Litopenaeus vannamei, temperature, pH and concentration of non-ionic ammonia are three important water quality factors, and there is a nonlinear coupling relationship among the three. Based on this coupling relationship, the water quality information fusion Agent structure and two-level information fusion algorithm are proposed. At the first level of the fusion algorithm, the forward reasoning mechanism is used to infer whether the water quality factor exceeds the standard based on the rule base. In the second level of the fusion algorithm, according to the coupling relation model of water quality factor, using database search and fixed step search strategy to find the appropriate temperature and pH value, through the online adjustment of temperature and pH value, the temperature, pH value, Non-ionic ammonia concentration adjusted to a reasonable range to meet the breeding requirements. The experimental results show that the information fusion algorithm can effectively regulate the breeding water quality and reduce the number of water changes.