{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:13:14Z","timestamp":1760242394776,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2017,6,27]],"date-time":"2017-06-27T00:00:00Z","timestamp":1498521600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Variable selection is a key step for eliminating redundant information in spectroscopy. Among various variable selection methods, the physarum network (PN) is a newly-introduced and efficient one. However, the whole spectrum has to be equally divided into sub-spectral bands in PN. These division criteria limit the selecting ability and prediction performance. In this paper, we transform the spectrum division problem into a clustering problem and solve the problem by using an affinity propagation (AP) algorithm, an adaptive clustering method, to find the optimized number of sub-spectral bands and the number of wavelengths in each sub-spectral band. Experimental results show that combining AP and PN together can achieve similar prediction accuracy with much less wavelength than what PN alone can achieve.<\/jats:p>","DOI":"10.3390\/a10030073","type":"journal-article","created":{"date-parts":[[2017,6,28]],"date-time":"2017-06-28T10:25:56Z","timestamp":1498645556000},"page":"73","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Variable Selection Using Adaptive Band Clustering and Physarum Network"],"prefix":"10.3390","volume":"10","author":[{"given":"Huanyu","family":"Chen","sequence":"first","affiliation":[{"name":"Chongqing Key Laboratory of Nonlinear Circuit and Intelligent Information Processing, Southwest University, Chongqing 400715, China"},{"name":"School of Electronic and Information Engineering, Southwest University, Chongqing 400715, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3805-4138","authenticated-orcid":false,"given":"Tong","family":"Chen","sequence":"additional","affiliation":[{"name":"Chongqing Key Laboratory of Nonlinear Circuit and Intelligent Information Processing, Southwest University, Chongqing 400715, China"},{"name":"School of Electronic and Information Engineering, Southwest University, Chongqing 400715, China"}]},{"given":"Zhihao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Chongqing Key Laboratory of Nonlinear Circuit and Intelligent Information Processing, Southwest University, Chongqing 400715, China"},{"name":"School of Electronic and Information Engineering, Southwest University, Chongqing 400715, China"}]},{"given":"Guangyuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Chongqing Key Laboratory of Nonlinear Circuit and Intelligent Information Processing, Southwest University, Chongqing 400715, China"},{"name":"School of Electronic and Information Engineering, Southwest University, Chongqing 400715, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,6,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1561\/2200000002","article-title":"Dimension reduction: Aguided tour","volume":"2","author":"Burges","year":"2010","journal-title":"Found. 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