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Computational analysis of movement behaviors of medaka (Oryzias latipes) after the treatments of copper by using fractal dimension and artificial neural networks

机译:用分形维数和人工神经网络处理铜处理后Medaka(Oryzias Laides)运动行为的计算分析

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Response behaviors of medaka were computationally analyzed before and after the treatments of copper at low concentration (1.0 mg/L). Parameters (e.g., speed, stop time, turning rate, etc) of the movement patterns were used as input for training the Multi-Layer Perceptron. Detection rates of the movement patterns such as 'Slow movement' and 'No movement' increased after the treatments. However, a higher degree of variation was observed in detection rates. Fractal dimension calculated from the movement data of individual specimens decreased consistently after the treatments. Higher consistency in fractal dimension was further achieved by using the data for collective rearing. Feasibility of behavioral monitoring was discussed in assessing toxic chemicals in environment.
机译:在低浓度(1.0mg / L)的铜处理之前和之后,Medaka的响应行为在计算上分析。运动模式的参数(例如,速度,停止时间,转速等)用作训练多层Perceptron的输入。在处理之后,运动模式的检测速率如“缓慢的运动”和“没有运动”增加。然而,在检测速率下观察到更高程度的变化。在治疗后,从单个样本的移动数据计算的分形尺寸始终如一地减少。通过使用集体饲养的数据进一步实现了分形维数的较高一致性。在评估环境中有毒化学品时讨论了行为监测的可行性。

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