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Updated: Jul 9, 2025

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
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响应表面方法和基于人工神经网络的算法基因对EP/US/GAC氧化过程在德克萨降解中的建模和优化的比较研究:适用于真实废水,电能消耗的应用

Mehdi Salari1, Ahmad Alahabadi2, Abolfazl Rahmani-Sani2

  • 1Department of Environmental Health Engineering, School of Public Health, Sabzevar University of Medical Sciences, Sabzevar, Iran; Leishmaniasis Research Center, Sabzevar University of Medical Sciences, Sabzevar, Iran.

Chemosphere
|December 2, 2023
PubMed
概括

本研究介绍了一种集成的电/颗粒活性炭 (EP/US/GAC) 工艺,用于有效地从废水中去除甲松 (DXM). 欧盟/美国/GAC系统在降解DXM和改善废水质量方面表现出高效率,为制药废水处理提供了一个有前途的解决方案.

关键词:
人工神经网络的人工神经网络德克萨米他是一种电气氧是一种电气氧.响应表面方法 响应表面方法超声波是一种超声波.

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