{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T17:38:35Z","timestamp":1772645915430,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T00:00:00Z","timestamp":1709769600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"2023 Guangxi Colleges and Universities Young and Middle-Aged Teachers\u2019 Scientific Research Basic Ability Improvement Project","award":["2023KY0055"],"award-info":[{"award-number":["2023KY0055"]}]},{"name":"2023 Guangxi Colleges and Universities Young and Middle-Aged Teachers\u2019 Scientific Research Basic Ability Improvement Project","award":["ZN2018007"],"award-info":[{"award-number":["ZN2018007"]}]},{"name":"2023 Guangxi Colleges and Universities Young and Middle-Aged Teachers\u2019 Scientific Research Basic Ability Improvement Project","award":["IFPIP-1481-611-1443"],"award-info":[{"award-number":["IFPIP-1481-611-1443"]}]},{"name":"Guangxi Humanities and Social Sciences Development Research Center","award":["2023KY0055"],"award-info":[{"award-number":["2023KY0055"]}]},{"name":"Guangxi Humanities and Social Sciences Development Research Center","award":["ZN2018007"],"award-info":[{"award-number":["ZN2018007"]}]},{"name":"Guangxi Humanities and Social Sciences Development Research Center","award":["IFPIP-1481-611-1443"],"award-info":[{"award-number":["IFPIP-1481-611-1443"]}]},{"name":"Institutional Fund Projects","award":["2023KY0055"],"award-info":[{"award-number":["2023KY0055"]}]},{"name":"Institutional Fund Projects","award":["ZN2018007"],"award-info":[{"award-number":["ZN2018007"]}]},{"name":"Institutional Fund Projects","award":["IFPIP-1481-611-1443"],"award-info":[{"award-number":["IFPIP-1481-611-1443"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A dendritic neuron model (DNM) is a deep neural network model with a unique dendritic tree structure and activation function. Effective initialization of its model parameters is crucial for its learning performance. This work proposes a novel initialization method specifically designed to improve the performance of DNM in classifying high-dimensional data, notable for its simplicity, speed, and straightforward implementation. Extensive experiments on benchmark datasets show that the proposed method outperforms traditional and recent initialization methods, particularly in datasets consisting of high-dimensional data. In addition, valuable insights into the behavior of DNM during training and the impact of initialization on its learning performance are provided. This research contributes to the understanding of the initialization problem in deep learning and provides insights into the development of more effective initialization methods for other types of neural network models. The proposed initialization method can serve as a reference for future research on initialization techniques in deep learning.<\/jats:p>","DOI":"10.3390\/s24061729","type":"journal-article","created":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T08:59:37Z","timestamp":1709801977000},"page":"1729","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Improving Classification Performance in Dendritic Neuron Models through Practical Initialization Strategies"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4368-1443","authenticated-orcid":false,"given":"Xiaohao","family":"Wen","sequence":"first","affiliation":[{"name":"Teachers College for Vocational and Technical Education, Guangxi Normal University, Guilin 541001, China"},{"name":"Faculty of Innovation Engineering, Macau University of Science and Technology, Macau 999078, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5408-8752","authenticated-orcid":false,"given":"Mengchu","family":"Zhou","sequence":"additional","affiliation":[{"name":"Faculty of Innovation Engineering, Macau University of Science and Technology, Macau 999078, China"},{"name":"Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3796-0294","authenticated-orcid":false,"given":"Aiiad","family":"Albeshri","sequence":"additional","affiliation":[{"name":"Department of Computer Science, King Abdulaziz University, Jeddah 21481, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8778-743X","authenticated-orcid":false,"given":"Lukui","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Accounting and Audit, Guangxi University of Finance and Economics, Nanning 530031, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3650-8450","authenticated-orcid":false,"given":"Xudong","family":"Luo","sequence":"additional","affiliation":[{"name":"Teachers College for Vocational and Technical Education, Guangxi Normal University, Guilin 541001, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9131-7076","authenticated-orcid":false,"given":"Dan","family":"Ning","sequence":"additional","affiliation":[{"name":"Teachers College for Vocational and Technical Education, Guangxi Normal University, Guilin 541001, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1109\/JAS.2021.1004392","article-title":"QoS prediction model of cloud services based on deep learning","volume":"9","author":"Huang","year":"2022","journal-title":"IEEE\/CAA J. 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