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首页> 外文会议>Joint Conference on Chemistry >The use of artificial neural network for modeling the decolourization of acid orange 7 solution of industrial by ozonation process
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The use of artificial neural network for modeling the decolourization of acid orange 7 solution of industrial by ozonation process

机译：用人工神经网络用臭氧处理工艺酸橙7溶液脱色

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摘要

Acid Orange 7 (A07) is one of the synthetic dye in the dyeing process in the textile industry. The use of this dye can produce wastewater which will be endangered if not treated well. Ozonation method is one technique to solve this problem. Ozonation is a waste processing techniques using ozone as an oxidizing agent. Variables used in this research is the ozone concentration, the initial concentration of A07, temperature, and pH. Based on the experimental result that the optimum value decolourization percentage is 80% when the ozone concentration is 560 mg/L, the initial concentration A07 is 14 mg/L, the temperature is 390 °C, and pH is 7,6. Decolourization efficiency of experimental results and predictions successfully modelled by the neural network architecture. The data used to construct a neural network architecture quasi newton one step secant as many as 31 data. A comparison between the predicted results of the designed ANN models and experiment was conducted. From the modeling results obtained MAPE value of 0.7763%. From the results of this artificial neural network architecture obtained the optimum value decolourization percentage in 80,64% when the concentration of ozone is 550 mg/L, the initial concentration A07 is 11 mg/L, the temperature is 41 °C, and the pH is 7.9.
机译：酸橙7（a07）是纺织工业中染色过程中的合成染料之一。这种染料的使用可以产生废水，如果未良好处理，这将被濒临灭绝。 ozonation方法是解决这个问题的一种技术。臭氧是一种使用臭氧作为氧化剂的废物处理技术。本研究中使用的变量是臭氧浓度，初始浓度A07，温度和pH值。基于实验结果，当臭氧浓度为560mg / L时，最佳值脱色百分比为80％，初始浓度A07为14mg / L，温度为390℃，pH为7,6。神经网络架构的实验结果的脱色效率和预测成功建模。用于构建神经网络架构的数据准备ePton一步秒，多达31个数据。进行了设计的ANN模型和实验的预测结果之间的比较。从建模结果获得0.7763％的Mape值。从这种人工神经网络建筑的结果，当臭氧浓度为550mg / L时，获得最佳值脱色率，以80,64％，初始浓度A07为11mg / L，温度为41°C，而且pH是7.9。

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