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| Accurate Prediction of Paracetamol and Ascorbic Acid Mixed Solutions Based onPSO-BSA Heuristic Algorithm |
| Guo Boyu, Bao Hanyang, Rao Zhikang, Liu Zhe, Xu Ying* |
| Institute of Instrument Science and Engineering, School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China |
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Abstract In this paper, an electrochemical detection method for simultaneous detection of paracetamol (PA) and ascorbic acid (AA) concentrations was investigated. Experimental data were collected through a three-electrode electrochemical workstation, and PBs/cMWCNTs/GCE electrochemical sensors were prepared using cyclic voltammetry (CV), which resulted in basic separation of the peak potentials of PA and AA. Differential pulse voltammetry (DPV) and chronoamperometry (CA) were used to conduct electrochemical detection of PA and AA mixed solutions with different concentrations, and typical electrochemical features and image features of the detection curves were extracted. Then, the improved particle swarm optimization-backtracking search algorithm (PSO-BSA) network was used to decouple the experimental data and construct an accurate prediction model for the concentration of PA and AA in the mixed sample. Finally, the simultaneous detection of PA and AA dual-chemical drugs was achieved. The R-Square (R2) of the prediction results reached 0.995, the root mean square error (RMSE) reached 0.137 mM, and the mean absolute error (MAE) reached 0.124 mM. The method proposed in this study has the advantages of easy operation, satisfactory goodness of fit, and high cost-effectiveness, which is conducive in achieving synergistic detection results of PA and AA mixed drugs and achieving accurate analysis of the components of a certain drug sample.
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Received: 08 April 2024
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