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A Preliminary Analysis for Improving Model Structure of Fuzzy Habitat Preference Model for Japanese Medaka (Oryzias latipes)

机译:日本MEDAKA(ORYZIAS LATIPES)模糊栖息地偏好模型改进模型结构的初步分析

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The present study examined a preliminary analysis for improving model structure of fuzzy habitat preference model for Japanese medaka (Oryzias latipes) dwelling in agricultural canals in Japan. The present model employed a simplified fuzzy reasoning method for evaluating habitat preference of the fish based on the relationship with physical habitat characteristics observed in the field survey. The model parameter was optimized by using a simple genetic algorithm, in which number of fuzzy membership function was fixed. In the present analysis, number of fuzzy membership function was changed while the other methods were fixed as the original model. The model performance was evaluated based on mean square error between observed and predicted fish population density, and by using two different data sets. As a result, there was no clear tradeoff between number of fuzzy membership functions and prediction accuracy. By contrast, calibration and validation results showed a slight tendency of tradeoff. Further studies on clarifying the tradeoffs would be necessary for improving the model structure in an effective way.
机译:本研究检测了改善日本Medaka(Oryzias Layipes)在日本农业运河居住的模糊栖息地偏好模型模型结构的初步分析。本模型采用了一种简化的模糊推理方法,用于基于现场调查中观察到的物理栖息地特征的关系来评估鱼类栖息地偏好。通过使用简单的遗传算法进行了优化了模型参数,在该遗传算法中修复了模糊隶属函数的数量。在本分析中,模糊隶属函数的数量在其他方法作为原始模型固定时改变。基于观察和预测的鱼群密度之间的均方误差和使用两个不同的数据集来评估模型性能。因此,模糊会员函数的数量与预测准确性之间没有明确的权衡。相比之下,校准和验证结果显示出略有权衡的趋势。有关澄清权衡的进一步研究是以有效的方式改善模型结构的必要条件。

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