{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T19:54:05Z","timestamp":1771530845251,"version":"3.50.1"},"reference-count":36,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2020,8,31]],"date-time":"2020-08-31T00:00:00Z","timestamp":1598832000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61533021"],"award-info":[{"award-number":["61533021"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61773403"],"award-info":[{"award-number":["61773403"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fundamental Research Funds for the Central Universities of Central South University","award":["2019zzts561"],"award-info":[{"award-number":["2019zzts561"]}]},{"name":"State Key Laboratory of High Performance Complex Manufacturing in Central South University","award":["ZZYJKT2019-14"],"award-info":[{"award-number":["ZZYJKT2019-14"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Excessive discharge of heavy metal ions will aggravate environment pollution and threaten human health. Thus, it is of significance to real-time detect metal ions and control discharge in the metallurgical wastewater. We developed an accurate and rapid approach based on the singular perturbation spectrum estimator and extreme gradient boosting (SPSE-XGBoost) algorithms to simultaneously determine multi-metal ion concentrations by UV\u2013vis spectrometry. In the approach, the spectral data is expanded by multi-order derivative preprocessing, and then, the sensitive feature bands in each spectrum are extracted by feature importance (VI score) ranking. Subsequently, the SPSE-XGBoost model are trained to combine multi-derivative features and to predict ion concentrations. The experimental results indicate that the developed \u201cExpand-Extract-Combine\u201d strategy can not only overcome problems of background noise and spectral overlapping but also mine the deeper spectrum information by integrating important features. Moreover, the SPSE-XGBoost strategy utilizes the selected feature subset instead of the full-spectrum for calculation, which effectively improves the computing speed. The comparisons of different data processing methods are conducted. It outcomes that the proposed strategy outperforms other routine methods and can profoundly determine the concentrations of zinc, copper, cobalt, and nickel with the lowest RMSEP. Therefore, our developed approach can be implemented as a promising mean for real-time and on-line determination of multi-metal ion concentrations in zinc hydrometallurgy.<\/jats:p>","DOI":"10.3390\/s20174936","type":"journal-article","created":{"date-parts":[[2020,8,31]],"date-time":"2020-08-31T11:53:49Z","timestamp":1598874829000},"page":"4936","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Simultaneous Determination of Metal Ions in Zinc Sulfate Solution Using UV\u2013Vis Spectrometry and SPSE-XGBoost Method"],"prefix":"10.3390","volume":"20","author":[{"given":"Fei","family":"Cheng","sequence":"first","affiliation":[{"name":"School of Automation, Central South University, Changsha 410083, China"}]},{"given":"Chunhua","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Automation, Central South University, Changsha 410083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2778-0022","authenticated-orcid":false,"given":"Can","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Automation, Central South University, Changsha 410083, China"},{"name":"State Key Laboratory of High Performance Complex Manufacturing, Changsha 410083, China"}]},{"given":"Lijuan","family":"Lan","sequence":"additional","affiliation":[{"name":"School of Automation, Central South University, Changsha 410083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0063-0363","authenticated-orcid":false,"given":"Hongqiu","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Automation, Central South University, Changsha 410083, China"}]},{"given":"Yonggang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Automation, Central South University, Changsha 410083, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.trac.2018.07.005","article-title":"Electrochemical spectral methods for trace detection of heavy metals: A review","volume":"106","author":"Chen","year":"2018","journal-title":"TrAC Trends. 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