A novel scheme for spectrum prediction in cognitive radio networks / Mehdi Askari and Rezvan Dastanian
An efficient spectrum prediction model is presented to improve the spectrum utilization in cognitive radio network. In this model, a novel improved version of Teaching-Learning-Based-Optimization algorithm, also referred to iTLBO algorithm, is proposed to train a feed forward artificial neural netwo...
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Universiti Teknologi MARA,
2021-10.
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LEADER | 00000 am a22000003u 4500 | ||
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001 | repouitm_52056 | ||
042 | |a dc | ||
100 | 1 | 0 | |a Askari, Mehdi |e author |
700 | 1 | 0 | |a Dastanian, Rezvan |e author |
245 | 0 | 0 | |a A novel scheme for spectrum prediction in cognitive radio networks / Mehdi Askari and Rezvan Dastanian |
260 | |b Universiti Teknologi MARA, |c 2021-10. | ||
500 | |a https://ir.uitm.edu.my/id/eprint/52056/1/52056.pdf | ||
520 | |a An efficient spectrum prediction model is presented to improve the spectrum utilization in cognitive radio network. In this model, a novel improved version of Teaching-Learning-Based-Optimization algorithm, also referred to iTLBO algorithm, is proposed to train a feed forward artificial neural network (ANN). The performance of the proposed iTLBO-ANN model is compared with some hybrid prediction models, including the genetic algorithm with ANN (GA-ANN), the firefly algorithm with ANN (FF-ANN), and the conventional TLBO algorithm with ANN (TLBO- ANN). Performance evaluation via a real-word spectrum data set (GSM-900) confirms that iTLBO-ANN outperforms other spectrum prediction schemes in terms of prediction error and prediction efficiency. | ||
546 | |a en | ||
690 | |a Radio | ||
690 | |a Radio frequency identification systems | ||
690 | |a Probes (Electronic instruments) | ||
655 | 7 | |a Article |2 local | |
655 | 7 | |a PeerReviewed |2 local | |
787 | 0 | |n https://ir.uitm.edu.my/id/eprint/52056/ | |
787 | 0 | |n https://jeesr.uitm.edu.my/ | |
856 | 4 | 1 | |u https://ir.uitm.edu.my/id/eprint/52056/ |z Link Metadata |