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Prediction of Water Quality Evaluation for Fish Ponds of Aquaculture

机译:水产养殖鱼塘水质评价预测

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This study used a regression method to build model for predicting water quality for the fish pond. From aquaculture practitioners' point of view, how to effectively control the water quality for the fish pond is very important. In basis of the experience of aquaculture practitioners, temperature, pH, conductivity, salinity, and last monitored oxygen content influence the water quality (here, called influencing factor). Life and death of fish are determined by water quality as well as water quality is decided by oxygen content. Therefore, the evaluation of the water quality is according to oxygen content. Regression method is often used for statistical analysis and prediction. In regression method, model is established by dependent variables and independent variables. In this study, the five influencing factors are represented as independent variables and the oxygen content is seen as dependent variable. From the experimental result, the oxygen content can be kept in the reasonable range.
机译:本研究采用回归方法来构建用于预测鱼塘水质的模型。从水产养殖从业者的观点来看,如何有效地控制鱼塘的水质非常重要。基于水产养殖从业者的经验,温度,pH,电导率,盐度和最后监测的氧气含量影响水质(这里,称为影响因子)。鱼的生死是通过水质确定的,水质由氧含量决定。因此,水质评估是根据氧含量的。回归方法通常用于统计分析和预测。在回归方法中,模型是由依赖变量和独立变量建立的。在本研究中,五种影响因素表示为独立变量,并且氧含量被视为依赖变量。从实验结果中,氧含量可以保持在合理的范围内。

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