{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T08:01:54Z","timestamp":1767168114870,"version":"build-2238731810"},"reference-count":25,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,6,30]],"date-time":"2021-06-30T00:00:00Z","timestamp":1625011200000},"content-version":"vor","delay-in-days":180,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100015260","name":"Macau University of Science and Technology","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100015260","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>In the human resource system of modern enterprises, human\u2010post matching big data occupies an important irreplaceable position. With the deepening of the reform of state\u2010owned enterprises, some shortcomings of human\u2010post matching big data have become prominent. The purpose of this article is to solve the current state\u2010owned enterprises. There are a variety of problems with big data in the enterprise, and an effective method is found that can accurately evaluate the degree of human\u2010job matching in state\u2010owned enterprises and provide a scientific basis for the manager of talent and resource allocation to make more rational decisions. Through the radial basis function (RBF) neural network\u2010based big data model of human\u2010post matching evaluation of state\u2010owned enterprises, we scientifically and effectively evaluate the matching degree of the quality and ability of the personnel with the relevant requirements of the position and then help the company to adjust the personnel at any time changes in positions to maximize the efficiency of human resources. In this paper, considering the actual situation of the enterprise, the RBF neural network and the analytic hierarchy process (AHP) method are used comprehensively. Firstly, the AHP is used to obtain the weight of each evaluation index in the human\u2010post matching index system. At the same time, the artificial neural network theory is self\u2010adapting. Learning is helpful to solve the problem that the AHP method is too subjective. The two learn from each other\u2019s strong points and combine their weaknesses organically to increase the convenience and effectiveness of evaluation.<\/jats:p>","DOI":"10.1155\/2021\/6025492","type":"journal-article","created":{"date-parts":[[2021,6,30]],"date-time":"2021-06-30T12:51:07Z","timestamp":1625057467000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["[Retracted] Optimization and Simulation of Enterprise Management Resource Scheduling Based on the Radial Basis Function (RBF) Neural Network"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1059-336X","authenticated-orcid":false,"given":"Ye","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaowen","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,6,30]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-017-1018-x"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.42.7.1082"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-017-1313-7"},{"key":"e_1_2_9_4_2","first-page":"29","article-title":"Reinforcement learning combined with radial basis function neural network to solve job-shop scheduling problem","volume":"11","author":"Williem R. S.","year":"2019","journal-title":"Business Innovation and Technology Management"},{"key":"e_1_2_9_5_2","first-page":"229","article-title":"Hybrid artificial intelligence system in constraint based scheduling of integrated manufacturing ERP systems","volume":"2","author":"Rojek I.","year":"2018","journal-title":"Hybrid Artificial Intelligence Systems"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.3233\/jifs-190749"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1142\/s0129065707000890"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1287\/ijoc.5.4.374"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.2174\/2352096514999210104144312"},{"key":"e_1_2_9_10_2","first-page":"1946","article-title":"Modeling and algorithm of data transmission system of ground station based on radial basis function neural network","volume":"32","author":"Chang F.","year":"2019","journal-title":"Systems Engineering and Electronics"},{"key":"e_1_2_9_11_2","first-page":"1907","article-title":"Short-term forecast of blast furnace gas production amount based on grey RBF neural network","volume":"713","author":"Lv Z. M.","year":"2018","journal-title":"Applied Mechanics and Materials"},{"key":"e_1_2_9_12_2","first-page":"1","article-title":"RBF neural network for the priority of buyer order in supply chain","volume":"8","author":"Tang L.","year":"2020","journal-title":"Wireless Communications, Networking and Mobile Computing"},{"key":"e_1_2_9_13_2","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1187\/3\/032109"},{"key":"e_1_2_9_14_2","first-page":"3","article-title":"Rainfall time series forecasting based on modular RBF neural network model coupled with SSA and PLS","volume":"6","author":"Yu J. W.","year":"2018","journal-title":"Journal of Theoretical and Applied Computer Science"},{"key":"e_1_2_9_15_2","first-page":"2","article-title":"Sub-engineering fee monte-carlo simulation method based on RBF neural network forecast","volume":"9","author":"Li L.","year":"2020","journal-title":"Journal of Railway Science and Engineering"},{"key":"e_1_2_9_16_2","first-page":"1","article-title":"Research on tangential stiffness modeling based on MPSO-RBF neural network algorithm","volume":"2","author":"Yang H.","year":"2019","journal-title":"Journal of Xi\u2019an University of Technology"},{"key":"e_1_2_9_17_2","first-page":"3","article-title":"System modeling of satellite ground station based on RBF neural networks","volume":"9","author":"Meng H.","year":"2020","journal-title":"Computer Simulation"},{"key":"e_1_2_9_18_2","doi-asserted-by":"publisher","DOI":"10.1080\/15325008.2011.615802"},{"key":"e_1_2_9_19_2","first-page":"933","article-title":"Research on yield forecasting model based on RBF in discrete manufacturing industry application","volume":"15","author":"Bi L.","year":"2020","journal-title":"Chemistry and Computer Engineering"},{"key":"e_1_2_9_20_2","first-page":"11","article-title":"Novel project evaluation model based on GAAA-RBF neural network","volume":"13","author":"Ye Q.","year":"2019","journal-title":"Mathematics in Practice and Theory"},{"key":"e_1_2_9_21_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.aml.2021.107417"},{"key":"e_1_2_9_22_2","first-page":"77","article-title":"An RBF-based neuro-fuzzy system for scenario planning in project management","volume":"11","author":"Khatibi V.","year":"2019","journal-title":"Financial Management and Economics"},{"key":"e_1_2_9_23_2","doi-asserted-by":"publisher","DOI":"10.1080\/13588265.2021.1889250"},{"key":"e_1_2_9_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.camwa.2020.01.014"},{"key":"e_1_2_9_25_2","doi-asserted-by":"publisher","DOI":"10.1007\/s41870-020-00492-y"}],"updated-by":[{"DOI":"10.1155\/2023\/9754050","type":"retraction","label":"Retraction","source":"retraction-watch","updated":{"date-parts":[[2023,6,28]],"date-time":"2023-06-28T00:00:00Z","timestamp":1687910400000},"record-id":"46965"},{"DOI":"10.1155\/2023\/9754050","type":"retraction","label":"Retraction","source":"publisher","updated":{"date-parts":[[2023,6,28]],"date-time":"2023-06-28T00:00:00Z","timestamp":1687910400000}}],"container-title":["Computational Intelligence and Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2021\/6025492.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2021\/6025492.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/2021\/6025492","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T07:37:23Z","timestamp":1722929843000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/2021\/6025492"}},"subtitle":[],"editor":[{"given":"Syed Hassan","family":"Ahmed","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":25,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["10.1155\/2021\/6025492"],"URL":"https:\/\/doi.org\/10.1155\/2021\/6025492","archive":["Portico"],"relation":{},"ISSN":["1687-5265","1687-5273"],"issn-type":[{"value":"1687-5265","type":"print"},{"value":"1687-5273","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"2021-06-02","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-06-22","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-06-30","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"6025492"}}