{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T10:44:28Z","timestamp":1782384268066,"version":"3.54.5"},"reference-count":33,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T00:00:00Z","timestamp":1705968000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61971248"],"award-info":[{"award-number":["61971248"]}],"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":["U20A20121"],"award-info":[{"award-number":["U20A20121"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100022963","name":"Key Research and Development Program of Zhejiang Province","doi-asserted-by":"publisher","award":["2020C03064"],"award-info":[{"award-number":["2020C03064"]}],"id":[{"id":"10.13039\/100022963","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","award":["LY22F010004"],"award-info":[{"award-number":["LY22F010004"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017549","name":"Science and Technology Innovation 2025 Major Project of Ningbo","doi-asserted-by":"publisher","award":["2023Z168"],"award-info":[{"award-number":["2023Z168"]}],"id":[{"id":"10.13039\/501100017549","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017549","name":"Science and Technology Innovation 2025 Major Project of Ningbo","doi-asserted-by":"publisher","award":["2023Z132"],"award-info":[{"award-number":["2023Z132"]}],"id":[{"id":"10.13039\/501100017549","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017549","name":"Science and Technology Innovation 2025 Major Project of Ningbo","doi-asserted-by":"publisher","award":["2022Z241"],"award-info":[{"award-number":["2022Z241"]}],"id":[{"id":"10.13039\/501100017549","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["analyticalsciencejournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Rapid Comm Mass Spectrometry"],"published-print":{"date-parts":[[2024,3,30]]},"abstract":"<jats:sec>\n                    <jats:title>Rationale<\/jats:title>\n                    <jats:p>Ion mobility spectrometry (IMS), as a promising analytical tool, has been widely employed in the structural characterization of biomolecules. Nevertheless, the inherent limitation in the structural resolution of IMS frequently results in peak overlap during the analysis of isomers exhibiting comparable structures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The radial basis function (RBF) neural network optimization algorithm based on dynamic inertial weight particle swarm optimization (DIWPSO) was proposed for separating overlapping peaks in IMS. The RBF network structure and parameters were optimized using the DIWPSO algorithm. By extensively training using a large dataset, an adaptive model was developed to effectively separate overlapping peaks in IMS data. This approach successfully overcomes issues related to local optima, ensuring efficient and precise separation of overlapping peaks.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The method's performance was evaluated using experimental validation and analysis of overlapping peaks in the IMS spectra of two sets of isomers: 3\u2032\/6\u2032\u2010sialyllactose; fructose\u20106\u2010phosphate, glucose\u20101\u2010phosphate, and glucose\u20106\u2010phosphate. A comparative analysis was conducted using other algorithms, including the sparrow search algorithm, DIWPSO algorithm, and multi\u2010objective dynamic teaching\u2010learning\u2010based optimization algorithm. The comparison results show that the DIWPSO\u2010RBF algorithm achieved remarkably low maximum relative errors of only 0.42%, 0.092%, and 0.41% for ion height, mobility, and half peak width, respectively. These error rates are significantly lower than those obtained using the other three algorithms.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The experimental results convincingly demonstrate that this method can adaptively, rapidly, and accurately separate overlapping peaks of multiple components, improving the structural resolution of IMS.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/rcm.9700","type":"journal-article","created":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T06:29:21Z","timestamp":1705991361000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Radial basis function neural network optimization algorithm based on dynamic inertial weight particle swarm optimization for separating overlapping peaks in ion mobility spectrometry"],"prefix":"10.1002","volume":"38","author":[{"given":"Binxin","family":"Shou","sequence":"first","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science Ningbo University  Ningbo P. R. China"},{"name":"Zhejiang Engineering Research Center of Advanced Mass Spectrometry and Clinical Application, Institute of Mass Spectrometry, School of Materials Science and Chemical Engineering Ningbo University  Ningbo P. R. China"},{"name":"Ningbo Zhenhai Institute of Mass Spectrometry  Ningbo P. R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingguang","family":"Yang","sequence":"additional","affiliation":[{"name":"Zhejiang Ningbo Ecological and Environmental Monitoring Center  Ningbo P. R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zihan","family":"Song","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science Ningbo University  Ningbo P. R. 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