{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:49:45Z","timestamp":1760240985929,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2019,11,4]],"date-time":"2019-11-04T00:00:00Z","timestamp":1572825600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61901409, 61961013, 61701144"],"award-info":[{"award-number":["61901409, 61961013, 61701144"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper investigates outage probability (OP) performance predictions using transmit antenna selection (TAS) and derives exact closed-form OP expressions for a TAS scheme. It uses Monte-Carlo simulations to evaluate OP performance and verify the analysis. A back-propagation (BP) neural network-based OP performance prediction algorithm is proposed and compared with extreme learning machine (ELM), locally weighted linear regression (LWLR), support vector machine (SVM), and BP neural network methods. The proposed method was found to have higher OP performance prediction results than the other prediction methods.<\/jats:p>","DOI":"10.3390\/s19214789","type":"journal-article","created":{"date-parts":[[2019,11,4]],"date-time":"2019-11-04T04:13:08Z","timestamp":1572840788000},"page":"4789","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Outage Probability Performance Prediction for Mobile Cooperative Communication Networks Based on Artificial Neural Network"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7347-3763","authenticated-orcid":false,"given":"Han","family":"Wang","sequence":"first","affiliation":[{"name":"College of Physical Science &amp; Engineering, Yichun University, Yichun 336000, China"},{"name":"Institute of Data Science, City University of Macau, Macau 999078, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2169-6356","authenticated-orcid":false,"given":"Lingwei","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Information Science &amp; Technology, Qingdao University of Science &amp; Technology, Qingdao 266061, China"},{"name":"Key Laboratory of Opto-Technology and Intelligent Control, Ministry of Education, Lanzhou Jiaotong University, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianpeng","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Hakou 570228, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5766","DOI":"10.1109\/JIOT.2019.2905788","article-title":"Assistant Vehicle Localization Based on Three Collaborative Base Stations via SBL Based Robust Estimation","volume":"6","author":"Wang","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"6348","DOI":"10.1109\/TWC.2018.2859394","article-title":"Multiple UAVs as Relays: Multi-hop single link versus multiple dual-hop links","volume":"17","author":"Chen","year":"2018","journal-title":"IEEE Trans. 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