MULTI-LAYER PERCEPTRON NEURAL NETWORK UHF FIELD STRENGTH PREDICTION MODEL FOR MAIDUGURI METROPOLIS

Auteur/ices

  • A. C. Deme
    Department of Computer Science, University of Jos, Nigeria
  • A. U. Usman
    Department of Electrical and Electronics Engineering, Federal University of Technology, P.M.B. 65, Minna , Nigeria
  • D. N. Choji
    Department of Computer Science, University of Jos , Nigeria

Résumé

This paper investigates the application of a Multi-layer Perceptron Neural Network (MLP-NN) based model for field strength prediction across the Maiduguri metropolis at an operating frequency of 1800MHz. Received power values obtained from multiple Base Transceiver Stations situated within the city were used to train, validate and test the MLP-NN for ability to generalize. Results indicate that the MLP-NN model with a Root Mean Squared Error (RMSE) value of 5.29dB offers an improvement over the COST 231 Walfisch-Ikegami model, which has an RMSE value of 7.95dB

Dimensions
front

Publiée

2023-11-11

Comment citer

MULTI-LAYER PERCEPTRON NEURAL NETWORK UHF FIELD STRENGTH PREDICTION MODEL FOR MAIDUGURI METROPOLIS. (2023). FULafia Journal of Science and Technology , 3(1), 118-125. https://lafiascijournals.org.ng/index.php/fjst/article/view/74

Numéro

Vol. 3 No 1 (2017): Fulafia Journal of Science and Technology (FJST)

Rubrique

Physical Sciences
Copyright & Licensing

Comment citer

MULTI-LAYER PERCEPTRON NEURAL NETWORK UHF FIELD STRENGTH PREDICTION MODEL FOR MAIDUGURI METROPOLIS. (2023). FULafia Journal of Science and Technology , 3(1), 118-125. https://lafiascijournals.org.ng/index.php/fjst/article/view/74

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