罗丹明B
光催化
均方误差
降级(电信)
辐照
人工神经网络
纳米颗粒
近似误差
材料科学
催化作用
罗丹明
平均绝对百分比误差
核化学
生物系统
化学工程
化学
纳米技术
数学
计算机科学
光学
统计
物理
有机化学
机器学习
工程类
荧光
电信
生物
核物理学
作者
P. Swapna Reddy,Susmita Das
标识
DOI:10.1002/ceat.202200374
摘要
Abstract An artificial neural network (ANN) model was developed for the photocatalytic degradation of rhodamine B by TiO 2 nanoparticles synthesized by the electrochemical method, under direct sunlight irradiation. The four inputs are: irradiation time, initial dye concentration, pH of the initial solution, and catalyst loading. The ANN model with 20 hidden neurons and with R 2 of 0.999 shows minimum values of the performance metrics of 0.169, 2.020, 1.531, and 0.215 for the mean square error, the root mean square error, the mean absolute error, and the mean absolute percentage error, respectively. The optimized ANN configuration of 4‐20‐1 shows a good fit with the experimental data. The result shows that the sunlight irradiation time has the main impact on rhodamine B degradation at ∼55 %.
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