{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:47:12Z","timestamp":1776811632086,"version":"3.51.2"},"reference-count":24,"publisher":"European Society of Computational Methods in Sciences and Engineering","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2022,5,13]]},"abstract":"<jats:p>In order to better promote the development of power enterprises and improve the modern communication means of remote control system, the power automation communication technology based on improved genetic algorithm is proposed. Based on the improved genetic algorithm, the power automation communication model is divided into master station model, communication model and terminal model. The main station of power automation communication is located in the power dispatching center. Through power communication or wireless public network, the collected data is transmitted to power automation for centralized processing. The structure of power automation communication equipment is optimized, and the power automation communication scheme is improved, so as to better realize the research of power automation communication. The experimental results show that the power automation communication technology based on improved genetic algorithm has high monitoring accuracy, can effectively eliminate noise, and has high practical application value.<\/jats:p>","DOI":"10.3233\/jcm-225963","type":"journal-article","created":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T13:27:22Z","timestamp":1646141242000},"page":"725-735","source":"Crossref","is-referenced-by-count":1,"title":["Power automation communication technology based on improved genetic algorithm"],"prefix":"10.66113","volume":"22","author":[{"given":"Lu","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"55691","reference":[{"issue":"1","key":"10.3233\/JCM-225963_ref1","first-page":"149","article-title":"Data augment method for power system transient stability assessment based on improved conditional generative adversarial network","volume":"43","author":"Tan","year":"2019","journal-title":"Autom Electr Power Syst."},{"issue":"2","key":"10.3233\/JCM-225963_ref2","doi-asserted-by":"crossref","first-page":"1683","DOI":"10.1109\/TPWRS.2017.2724058","article-title":"Multi-objective mixed-integer dynamic optimization method applied to optimal allocation of dynamic var sources of power systems","volume":"33","author":"Deng","year":"2018","journal-title":"IEEE Trans Power Syst."},{"issue":"2","key":"10.3233\/JCM-225963_ref3","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1109\/MPEL.2020.2988077","article-title":"Power electronics design methods and automation in the digital era: Evolution of design automation tools","volume":"7","author":"Cardoso","year":"2020","journal-title":"IEEE Power Electr Mag."},{"issue":"1","key":"10.3233\/JCM-225963_ref4","first-page":"20","article-title":"New traffic classification method for imbalanced network data","volume":"38","author":"Yan","year":"2018","journal-title":"J Comput Appl."},{"key":"10.3233\/JCM-225963_ref5","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/j.cose.2017.06.012","article-title":"A novel privacy preserving user identification approach for network traffic","volume":"70","author":"Clarke","year":"2017","journal-title":"Comput Secur."},{"issue":"3","key":"10.3233\/JCM-225963_ref6","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1504\/IJES.2018.091786","article-title":"Electric power communication bandwidth prediction based on adaptive extreme learning machine","volume":"10","author":"Di","year":"2018","journal-title":"Int J Embedded Syst."},{"key":"10.3233\/JCM-225963_ref7","unstructured":"Wang T, Sun C, Gu X, Qin X. 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