發(fā)布者：抗性基因網(wǎng) 時間：2023-06-12 瀏覽量：498
摘要
? ? ? 抗生素和抗生素抗性基因（ARGs）在水生環(huán)境中經(jīng)常被檢測到，并被視為新出現(xiàn)的污染物?；诜聪騻鞑ド窠?jīng)網(wǎng)絡(luò)（BPNN），通過訓(xùn)練輸入和輸出，構(gòu)建了膜分離技術(shù)對四種目標(biāo)抗生素去除效果的預(yù)測模型?？股氐哪し蛛x試驗表明，微濾對阿奇霉素和環(huán)丙沙星的去除效果較好，基本在80%以上。超濾和納濾對磺胺甲惡唑（SMZ）和四環(huán)素（TC）的去除效果較好。滲透物中SMZ和TC的濃度之間存在很強(qiáng)的相關(guān)性，訓(xùn)練和驗證過程的R2超過0.9。輸入層變量與預(yù)測目標(biāo)之間的相關(guān)性越強(qiáng)，BPNN模型的預(yù)測性能就越好。這些結(jié)果表明，所建立的BPNN預(yù)測模型能夠更好地模擬膜分離技術(shù)對目標(biāo)抗生素的去除。該模型可用于預(yù)測和探索外部條件對膜分離技術(shù)的影響，為BPNN模型在環(huán)境保護(hù)中的應(yīng)用提供一定的依據(jù)。
Abstract
Antibiotics and antibiotic resistance genes (ARGs) have been frequently detected in the aquatic environment and are regarded as emerging pollutants. The prediction models for the removal effect of four target antibiotics by membrane separation technology were constructed based on back propagation neural network (BPNN) through training the input and output. The membrane separation tests of antibiotics showed that the removal effect of microfiltration on azithromycin and ciprofloxacin was better, basically above 80%. For sulfamethoxazole (SMZ) and tetracycline (TC), ultrafiltration and nanofiltration had better removal effects. There was a strong correlation between the concentrations of SMZ and TC in the permeate, and the R2 of the training and validation processes exceeded 0.9. The stronger the correlation between the input layer variables and the prediction target was, the better the prediction performances of the BPNN model than the nonlinear model and the unscented Kalman filter model were. These results showed that the established BPNN prediction model could better simulate the removal of target antibiotics by membrane separation technology. The model could be used to predict and explore the influence of external conditions on membrane separation technology and provide a certain basis for the application of the BPNN model in environmental protection.
https://www.tandfonline.com/doi/abs/10.1080/10934529.2023.2200719