A Novel Symmetrical Peak Fitting Method Based on Improved WOA Algorithm for the Analysis of Microchip Electrophoresis Signals

Abstract

The problem of overlapping peaks has been a challenge in microchip electrophoresis (ME) signal analysis. However, traditional peak fitting algorithms have difficulty analyzing overlapping peaks due to the high dependence on the starting point. In this study, we propose a symmetrical peak fitting method named the tent-mapped whale optimization algorithm and Levenberg–Marquardt (TWOALM), which combines a whale optimization algorithm (WOA) improved by one of the most commonly used chaotic maps, the tent map and the Levenberg–Marquardt (LM) algorithm. Specifically, we first derive the fitted model for the overlapping peaks, showing that it is separable nonlinear least squares, significantly reducing the number of parameters to be optimized. Second, we integrate the tent map into the WOA, which improves the convergence speed of the peak fitting algorithm. Finally, we propose an efficient peak-fitting algorithm that combines the improved WOA and LM. The advantage of the proposed algorithm is that it is significantly faster than WOA and significantly more accurate than the LM algorithm. The results of fitting the synthetic peaks and ME signals showed that the combination of the chaotic map-based WOA algorithm and the LM algorithm can significantly improve the peak fitting performance and provide an effective solution for the analysis of overlapping peaks.

A Novel Overlapping ME Peaks Decomposition Algorithm Based on Iterative Derivative Sharpening

“…To demonstrate the effectiveness of the proposed peak sharpening method, the fitting performance of different algorithms is compared in this section. For the overlapping peak fitting problem, the fitting accuracy of the swarm intelligence algorithms (SLSMA [7], TWOA [8], and PSO [9]), the gradient algorithms (LM [10] and TRR [11]), and the simplex algorithm (NM [12]) are analyzed. Consistent with previous work [7], the population size and maximum number of iterations for the swarm intelligence algorithms in this study are set to 250 and 200, respectively.…”

“…In the last five years, the analysis methods of peak-shaped signals based on optimization algorithms have been proposed. These methods can be classified into three categories, namely, swarm intelligence algorithms [7], [8], [9], gradient algorithms [10], [11], and simplex algorithm [12]. Specifically, the SLSMA [7] and the TWOA [8] were used for the fitting analysis of overlapping ME peaks by exploiting the global optimization capability of the swarm intelligence algorithm.…”

“…These methods can be classified into three categories, namely, swarm intelligence algorithms [7], [8], [9], gradient algorithms [10], [11], and simplex algorithm [12]. Specifically, the SLSMA [7] and the TWOA [8] were used for the fitting analysis of overlapping ME peaks by exploiting the global optimization capability of the swarm intelligence algorithm. Furthermore, the PSO algorithm [9] based peak detection method for chewing signals analysis also extends the application of swarm intelligence algorithms.…”

A Novel Unresolved Peaks Analysis Algorithm for ME Signal Detection Based on Improved SMA

“…To separate the unresolved peaks of magnetic eddy current signal, Xiong et al [17] proposed an unresolved peaks separation algorithm based on the genetic algorithm (GA). Recently, an improved whale optimization algorithm [18] has been applied to the analysis of ME signals. These studies show that the advantages of swarm intelligence algorithms in nonlinear optimization contribute to the analysis of unresolved peaks.…”

“…However, the SMA algorithm may also suffer from slow convergence when dealing with complex problems [20]. Although it has been shown that the problem of unresolved peaks analysis is a separable nonlinear least squares problem [18], [21], when there are more complex unresolved peaks, the larger number of nonlinear parameters to be optimized is a great challenge for the swarm intelligence algorithm. In addition, to our knowledge, no relevant studies are using the SMA algorithm to analyze unresolved peaks.…”