1. Hebei Province Key Laboratory of Test/Measurement Technology and Instrument, School of Electrical Engineering, YanshanUniversity, Qinhuangdao, Hebei 066004, China
2. Key Laboratory of Special Fiber and Fiber Sensor of Hebei Province, School of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
3. Center for Hydrogeology & Environmental Geology, Geological Environment Monitoring Engineering Technology Innovation Center of The Ministry of Natural Resources, Baoding, Hebei 071051, China
Abstract：Aiming at the difficulties in modeling the element concentration caused by the overlapping peaks of Pb and As in X-ray fluorescence spectroscopy (XRF) and the weak robustness of the crow search algorithm (CSA), the Gaussian mixture model (GMM) is combined with the improved the crow search algorithm (ICSA) to achieve the decomposition of overlapping peaks. Compared with CSA, ICSA has three main improvements: the introduction of the “crow feeding” feature to better connect GMM and ICSA; the fixed probability of awareness is changed to a gradient type to make the population iteration more diverse; appropriate adjustments the global optimization strategy makes the algorithm more stable and converges faster. The comparison experiment between the GMM model and the GMM-ICSA model shows that the decomposition accuracy of the optimized model is increased by 4.93%. At the same time, the mean square error and iteration time are used to measure the quality of the search algorithm, and ICSA is compared with the same type comparative experiments on the four algorithms show that the mean square error and iteration time of ICSA are better than other algorithms, which shows the feasibility of the improved algorithm in dealing with the problem of overlapping peaks.
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2021, Vol. 42 
