An improved stochastic configuration network algorithm and application

An improved stochastic configuration network algorithm and application | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 8 June 2025 V1 Latest version Share on An improved stochastic configuration network algorithm and application Authors : Huang Xiaodi , Jiang Yanchen , Li Qiansheng , Li Jun , and Wang Yongfu [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.174940802.21876857/v1 258 views 248 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract The Stochastic Configuration Network (SCN) is a universal approximator that stochastically configures the input weights and biases of hidden nodes under a supervised mechanism. This paper extends the original SCN to improve the learning efficiency by optimizing the configuration of hidden node parameters and expanding the training dataset with unlabeled data. Firstly, Randomly configuring hidden nodes parameters introduces uncertainty and does not achieve optimal values. To address this limitation, this paper introduces an improved Pelican Optimization Algorithm (IPOA) to enhance its global optimization capability, which is then applied to optimize the hidden nodes configuration. This improvement boosts network learning efficiency and results in a more lightweight structure. To address the challenge of limited labeled data for fully supervised SCN models, a semi-supervised learning approach is employed, using a small amount of labeled data to classify unlabeled data. Finally, the improved SCN (ISCN) algorithm is applied to a real-world industrial process for predicting the setpoint of coal mill outlet temperature in power system. Simulation results and real-world power plant applications demonstrate that the ISCN achieves faster convergence and improved generalization ability compared to the original SCN. Supplementary Material File (manuscript.pdf) Download 19.89 MB Information & Authors Information Version history V1 Version 1 08 June 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords coal mill outlet temperature optimization semi-supervised learning stochastic configuration network Authors Affiliations Huang Xiaodi Northeastern University School of Mechanical Engineering and Automation View all articles by this author Jiang Yanchen Huaneng Power International Inc View all articles by this author Li Qiansheng Huaneng Power International Inc View all articles by this author Li Jun Huaneng Power International Inc View all articles by this author Wang Yongfu [email protected] Northeastern University School of Mechanical Engineering and Automation View all articles by this author Metrics & Citations Metrics Article Usage 258 views 248 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Huang Xiaodi, Jiang Yanchen, Li Qiansheng, et al. An improved stochastic configuration network algorithm and application. Authorea . 08 June 2025. DOI: https://doi.org/10.22541/au.174940802.21876857/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. 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