{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T14:55:30Z","timestamp":1775746530673,"version":"3.50.1"},"reference-count":22,"publisher":"Springer Science and Business Media LLC","issue":"S1","license":[{"start":{"date-parts":[[2018,2,23]],"date-time":"2018-02-23T00:00:00Z","timestamp":1519344000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2019,1]]},"DOI":"10.1007\/s10586-018-1978-5","type":"journal-article","created":{"date-parts":[[2018,2,23]],"date-time":"2018-02-23T11:52:36Z","timestamp":1519386756000},"page":"157-163","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Optimized neural network for spectrum prediction using genetic algorithm in cognitive radio networks"],"prefix":"10.1007","volume":"22","author":[{"given":"P.","family":"Supraja","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"V. M.","family":"Gayathri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"R.","family":"Pitchai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,2,23]]},"reference":[{"key":"1978_CR1","doi-asserted-by":"crossref","unstructured":"Akbar, I., Tranter, W. H.: Dynamic spectrum allocation in cognitive radio using hidden Markov models: Poisson distributed case. In: Proceedings IEEE Southeast Conference, pp. 196\u2013201 (2007)","DOI":"10.1109\/SECON.2007.342884"},{"key":"1978_CR2","doi-asserted-by":"crossref","unstructured":"Chatziantoniou, E., Allen, B., Velisavljevic, V.: An HMM-based spectrum occupancy predictor for energy efficient cognitive radio. In: IEEE 24th International Conference on Personal Indoor and Mobile Radio Communications, pp. 601\u2013605 (2013)","DOI":"10.1109\/PIMRC.2013.6666207"},{"key":"1978_CR3","first-page":"849","volume":"12","author":"VK Tumuluru","year":"2010","unstructured":"Tumuluru, V.K., Wang, P., Niyato, D.: Channel status prediction for cognitive radio networks. Wirel. Commun. Mob. Comput. 12, 849\u2013942 (2010)","journal-title":"Wirel. Commun. Mob. Comput."},{"key":"1978_CR4","doi-asserted-by":"crossref","unstructured":"Jianli, Z., Mingwei, W.,Jinsha, Y.: Based on neural network spectrum prediction of Cognitive Radio. In: Electronics, Communications and Control International Conference (IECC) (2011)","DOI":"10.1109\/ICECC.2011.6066613"},{"key":"1978_CR5","unstructured":"Yin, L., Yin, S., Hong, W., Li, S.: Spectrum behavior learning in cognitive radio based on artificial neural network. In: Military Communication Conference, Track 1, Waveforms and Signal Processing (2011)"},{"key":"1978_CR6","first-page":"206","volume":"1","author":"Ms Dharmistha","year":"2012","unstructured":"Dharmistha, Ms, Vishwakarma, D.: Genetic algorithm based weights optimization of artificial neural network. Int. J. Adv. Res. Electr. Electr. Instrum. Eng. 1, 206\u2013211 (2012)","journal-title":"Int. J. Adv. Res. Electr. Electr. Instrum. Eng."},{"issue":"11","key":"1978_CR7","doi-asserted-by":"publisher","first-page":"4487","DOI":"10.1109\/TCOMM.2016.2607741","volume":"64","author":"A Tayel","year":"2016","unstructured":"Tayel, A., Rabia, S.I., Abouelseoud, Y.: An optimized hybrid approach for spectrum handoff in cognitive radio networks with non-identical channels. IEEE Trans. Commun. 64(11), 4487 (2016)","journal-title":"IEEE Trans. Commun."},{"issue":"11","key":"1978_CR8","doi-asserted-by":"publisher","first-page":"2814","DOI":"10.1109\/JSAC.2016.2615258","volume":"34","author":"PK Sahoo","year":"2016","unstructured":"Sahoo, P.K., Sahoo, D.: Sequence-based channel hopping algorithms for dynamic spectrum sharing in cognitive radio networks. IEEE J. Sel. Areas Commun. 34(11), 2814\u20132828 (2016)","journal-title":"IEEE J. Sel. Areas Commun."},{"issue":"4","key":"1978_CR9","doi-asserted-by":"publisher","first-page":"2471","DOI":"10.1109\/TVT.2015.2421913","volume":"65","author":"Y Lu","year":"2016","unstructured":"Lu, Y., Duel-Hallen, A.: Channel-aware spectrum sensing and access for mobile cognitive radio ad hoc networks. IEEE Trans. Veh. Technol. 65(4), 2471\u20132480 (2016)","journal-title":"IEEE Trans. Veh. Technol."},{"issue":"2","key":"1978_CR10","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1109\/JCN.2014.000032","volume":"16","author":"J Lee","year":"2014","unstructured":"Lee, J., Park, H.K.: Channel prediction-based channel allocation scheme for multichannel cognitive radio networks. J. Commun. Netw. 16(2), 209\u2013216 (2014)","journal-title":"J. Commun. Netw."},{"key":"1978_CR11","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.neunet.2016.01.001","volume":"77","author":"Y Luo","year":"2016","unstructured":"Luo, Y., Wang, Z., Wei, G., Alsaadi, F.E., Hayat, T.: State estimation for a class of artificial neural networks with stochastically corrupted measurements under Round-Robin protocol. Neural Netw. 77, 70\u201379 (2016)","journal-title":"Neural Netw."},{"key":"1978_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2017.09.018","author":"M Zareapoor","year":"2016","unstructured":"Zareapoor, M., Shamsolmoali, P., Jain, D.K., Wang, H., Yang, J.: Kernelized support vector machine with deep learning: an efficient approach for extreme multiclass dataset. Pattern Recognit. Lett. (2017). \n                    https:\/\/doi.org\/10.1016\/j.patrec.2017.09.018","journal-title":"Pattern Recognit. Lett."},{"key":"1978_CR13","unstructured":"Biserni, C., Dalpiaz, F. L., Fagundes, T. M., Rocha, L. A. O.: (2017)"},{"key":"1978_CR14","doi-asserted-by":"crossref","unstructured":"Eberhart, R. C., Shi, Y.: Comparison Between Genetic Algorithms and Particle Swarm Optimization. In: Proceedings of the 7th International Conference on Evolutionary Programming VII, vol. 1447, pp. 611\u2013616. Springer, London","DOI":"10.1007\/BFb0040812"},{"issue":"1","key":"1978_CR15","doi-asserted-by":"publisher","first-page":"29","DOI":"10.15866\/iremos.v9i1.8029","volume":"9","author":"A Boultif","year":"2016","unstructured":"Boultif, A., Kabouche, A., Ladjel, S.: Application of genetic algorithms (GA) and threshold acceptance (TA) to a ternary liquid-liquid equilibrium system. Int. Rev. Model. Simul (IREMOS) 9(1), 29\u201336 (2016)","journal-title":"Int. Rev. Model. Simul (IREMOS)"},{"key":"1978_CR16","doi-asserted-by":"crossref","unstructured":"Mamdoohi, G., Saryazdi, S.: Optimization of Multi-Wavelength Brillouin-Raman Fiber Laser in NALM Design By Employment Genetic Algorithm. In: 2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC), pp. 26\u201328. IEEE, New York (2017)","DOI":"10.1109\/CSIEC.2017.7940178"},{"issue":"7","key":"1978_CR17","doi-asserted-by":"publisher","first-page":"3183","DOI":"10.1007\/s12206-017-0607-1","volume":"31","author":"N Romero","year":"2017","unstructured":"Romero, N., Fl\u00f3rez, E., Mendoza, L.: Optimization of a multi-link steering mechanism using a continuous genetic algorithm. J. Mech. Sci. Technol. 31(7), 3183\u20133188 (2017)","journal-title":"J. Mech. Sci. Technol."},{"issue":"2","key":"1978_CR18","doi-asserted-by":"publisher","first-page":"1517","DOI":"10.1007\/s10586-017-0859-7","volume":"20","author":"S Zhang","year":"2017","unstructured":"Zhang, S., Wang, H., & Huang, W.: Two-stage plant species recognition by local mean clustering & Weighted sparse representation classification. Clust. Comput. 20(2), 1517\u20131525 (2017)","journal-title":"Clust.Comput."},{"key":"1978_CR19","volume-title":"Genetic Algorithms in Search, Optimization, and Machine Learning [M]","author":"DE Goldberg","year":"1989","unstructured":"Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning [M]. Addison-Wesley Pub. Co., Boston (1989)"},{"key":"1978_CR20","unstructured":"Zhang, Q., Wang, C.: Using genetic algorithm to optimize artificial neural network: a case study on earthquake prediction. In: International Conference on Genetic and Evolutionary Computing"},{"key":"1978_CR21","doi-asserted-by":"publisher","DOI":"10.1007\/s11277-016-3818-3","author":"P Supraja","year":"2017","unstructured":"Supraja, P., Jayashri, S.: Optimized neural network for spectrum prediction scheme in cognitive radio. Wirel. Pers. Commun. (2017). \n                    https:\/\/doi.org\/10.1007\/s11277-016-3818-3\n                    \n                  . (ISSN:0929-6212)","journal-title":"Wirel. Pers. Commun."},{"key":"1978_CR22","doi-asserted-by":"publisher","DOI":"10.1007\/s11036-017-0909-7","author":"P Supraja","year":"2017","unstructured":"Supraja, P., Pitchai, R.: Spectrum prediction in cognitive radio with hybrid optimized neural network. Mob. Netw. Appl. (2017). \n                    https:\/\/doi.org\/10.1007\/s11036-017-0909-7","journal-title":"Mob. Netw. Appl."}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10586-018-1978-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-018-1978-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-018-1978-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,12]],"date-time":"2019-09-12T12:10:40Z","timestamp":1568290240000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10586-018-1978-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,2,23]]},"references-count":22,"journal-issue":{"issue":"S1","published-print":{"date-parts":[[2019,1]]}},"alternative-id":["1978"],"URL":"https:\/\/doi.org\/10.1007\/s10586-018-1978-5","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,2,23]]},"assertion":[{"value":"9 October 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 January 2018","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 February 2018","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 February 2018","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}