Decomposition of overlapping peaks in X-ray fluorescence using improved crow searching algorithm based on opposite learning
JOURNAL OF CHEMOMETRICS(2021)
摘要
To overcome the difficulties in overlapping peaks decomposition in X-ray fluorescence (XRF) spectrum of heavy metal Pb and As, an improved crow searching algorithm (CSA) (ICSA) method was proposed. Compared with the CSA, three main improvements were performed: the opposite learning (OL) mechanism was introduced to expand the diversity of population and the parameter TF was introduced to control the convergence, which could avoid falling into the local minimum during the initialization process. Furthermore, this method has made some adjustments on the global optimization strategy, which can make the convergence more stable. When using the ICSA to decompose the overlapping peaks, the resolution accuracy improved by 2.23%, and the mean square error is better than other four algorithms of the same type, showing the feasibility of ICSA in dealing with the overlapping peaks.
更多查看译文
关键词
heavy metal, improved CSA, opposite learning, overlapping peaks decomposition, X-ray fluorescence spectroscopy
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要