This inquiry focuses on acquiring empirical models to predict ciprofloxacin removal using magnetization of functionalized multi-walled carbon nanotubes (FMWCNTs-Fe₃O₄) from an aqueous solution. The response surface methodology (RSM) and support vector regression (SVR) as data mining techniques were adopted to develop models. Critical parameter effects comprising pH (3 - 10), adsorbent dose (0.2 – 1 g/L), contact time (5 - 60 min) and ciprofloxacin concentrations (30-100 mg/L) were analysed. The Langmuir, Freundlich, Temkin and Dubinin-Radushkevich isothermal models were utilized to fit the empirical data. FMWCNTs-Fe₃O₄ prepared by chemical co-precipitation method was loaded by Fe₃O₄ nanoparticles (using sonication) to synthesize functionalized multi-walled carbon nanotubes to remove ciprofloxacin (CIP). FMWCNTs-Fe₃O₄ were characterized by fourier transform infrared spectroscopy (FTIR), X-Ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope (TEM), vibrating sample magnetometer (VSM) methods. The Langmuir model was utilized to precisely describe the maximum adsorption capacity(q_max) of 107.66 mg/g with R² =0.998. In this study, the pseudo-second-order model exactly described the adsorption process(R²= 0.99). The results illustrated that the LSSVM (least squares support vector machine) model efficiently predicted the CIP removal percentage with very high accuracy in the training phase (R²=0.975) and the test phase (R²=0.970). Moreover, the highest removal percentages in optimized step were achieved for RSM (pH 5.4, dose 0.78 g/L, time of 24.5 min, and CIP concentrations of 59 mg/L) and GA (genetic algorithm) (pH 4.4, dose 0.74 g/L, time of 42 min, and CIP concentrations of 38 mg/L) techniques by 88 and 99.1%, respectively. The FMCNTs-Fe₃O₄ efficiency has decreased by 12% even after five used cycles relative to the optimal conditions (regeneration). Therefore, FMWCNTs-Fe₃O₄ adsorption was considered to be an effective technique for CIP removal in the aqueous environment.

这项研究的重点是获得经验模型，以预测使用功能化多壁碳纳米管（FMWCNTs-Fe ₃ O ₄）从水溶液中磁化的环丙沙星清除率。采用响应面方法（RSM）和支持向量回归（SVR）作为数据挖掘技术来开发模型。分析了关键参数的影响，包括pH（3-10），吸附剂剂量（0.2-1  g / L），接触时间（5-60 分钟）和环丙沙星浓度（30-100  mg / L）。利用Langmuir，Freundlich，Temkin和Dubinin-Radushkevich等温模型拟合经验数据。通过化学共沉淀法制备的FMWCNTs-Fe ₃ O ₄负载Fe ₃O ₄纳米颗粒（使用超声处理）合成功能化的多壁碳纳米管，以去除环丙沙星（CIP）。通过傅里叶变换红外光谱（FTIR），X射线衍射（XRD），扫描电子显微镜（SEM），透射电子显微镜（TEM），振动样品磁力计（VSM）方法对FMWCNTs-Fe ₃ O ₄进行了表征。用Langmuir模型精确描述了最大吸附容量（q _max）为107.66  mg / g，R ² = 0.998。在这项研究中，伪二级模型准确地描述了吸附过程（R ²= 0.99）。结果表明，LSSVM（最小二乘支持向量机）模型在训练阶段（R ² = 0.975）和测试阶段（R ² = 0.970）以非常高的精度有效地预测了CIP去除百分比。此外，对于RSM（pH 5.4，剂量0.78  g / L，时间24.5 分钟，CIP浓度为59  mg / L）和GA（遗传算法）（pH 4.4，剂量0.74  g ），在优化步骤中达到了最高去除率。/ L，42 分钟的时间和38  mg / L的CIP浓度）分别降低了88％和99.1％。FMCNTs-Fe ₃ O ₄相对于最佳条件（再生），即使经过五个使用周期，效率也降低了12％。因此，FMWCNTs-Fe ₃ O ₄吸附被认为是在水性环境中去除CIP的有效技术。