{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:29:59Z","timestamp":1772252999531,"version":"3.50.1"},"reference-count":24,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2021,8,28]],"date-time":"2021-08-28T00:00:00Z","timestamp":1630108800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Research on Intelligent  Assessment Method of Equipment Capability Based on Key Elements of Index","award":["61977059"],"award-info":[{"award-number":["61977059"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Capability assessment plays a crucial role in the demonstration and construction of equipment. To improve the accuracy and stability of capability assessment, we study the neural network learning algorithms in the field of capability assessment and index sensitivity. Aiming at the problem of overfitting and parameter optimization in neural network learning, the paper proposes an improved machine learning algorithm\u2014the Ensemble Learning Based on Policy Optimization Neural Networks (ELPONN) with the policy optimization and ensemble learning. This algorithm presents an optimized neural network learning algorithm through different strategies evolution, and builds an ensemble learning model of multi-intelligent algorithms to assess the capability and analyze the sensitivity of the indexes. Through the assessment of capabilities, the algorithm effectively avoids parameter optimization from entering the minimum point in performance to improve the accuracy of equipment capability assessment, which is significantly better than previous neural network assessment methods. The experimental results show that the mean relative error is 4.10%, which is better than BP, GABP, and early stopping. The ELPONN algorithm has better accuracy and stability performance, and meets the requirements of capability assessment.<\/jats:p>","DOI":"10.3390\/s21175802","type":"journal-article","created":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T22:58:15Z","timestamp":1630450695000},"page":"5802","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Ensemble Learning Based on Policy Optimization Neural Networks for Capability Assessment"],"prefix":"10.3390","volume":"21","author":[{"given":"Feng","family":"Zhang","sequence":"first","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, No. 3888, Dongnanhu Rd., Changchun 130033, China"},{"name":"University of Chinese Academy of Sciences, No. 19, Yuquan Rd., Beijing 100049, China"},{"name":"School of Aviation Operations and Services, Aviation University of Air Force, No. 2222, Dongnanhu Rd., Changchun 130022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiang","family":"Li","sequence":"additional","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, No. 3888, Dongnanhu Rd., Changchun 130033, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ye","family":"Wang","sequence":"additional","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, No. 3888, Dongnanhu Rd., Changchun 130033, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lihong","family":"Guo","sequence":"additional","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, No. 3888, Dongnanhu Rd., Changchun 130033, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongyan","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Aviation Operations and Services, Aviation University of Air Force, No. 2222, Dongnanhu Rd., Changchun 130022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Wu","sequence":"additional","affiliation":[{"name":"PLA96901 Unit, No. 109, Beiqing Street, Haidian District, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongwei","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer Science, Jilin University, No. 2699, Qianjing Rd., Changchun 130012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,28]]},"reference":[{"key":"ref_1","unstructured":"Davis, P.K. 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