Path Loss Modeling: A Machine Learning Based Approach Using Support Vector Regression and Radial Basis Function Models-Reference-Cited by-同舟云学术

Path Loss Modeling: A Machine Learning Based Approach Using Support Vector Regression and Radial Basis Function Models

Published:2022 Issue:06 Volume:12 Page:990-1010
ISSN:2165-3917
Container-title:Open Journal of Applied Sciences
language:
Short-container-title:OJAppS

Author:

Ojo Stephen,Sari Arif,Ojo Taiwo P.

Publisher

Scientific Research Publishing, Inc.

Subject

Materials Chemistry

Reference36 articles.

1. Propagation Measurement System and Approach at 140 GHz-Moving to 6G and Above 100 GHz

2. Information and Communications Technologies for Sustainable Development Goals: State-of-the-Art, Needs and Perspectives

3. RADIO FREQUENCY OPTIMIZATION OF MOBILE NETWORKS IN ABEOKUTA, NIGERIA FOR IMPROVED QUALITY OF SERVICE

4. Obot, O.S. and Afolayan, J. (2011) Comparative Analysis of Path Loss Prediction Models for Urban Macrocellular Environments. Nigerian Journal of Technology, 30, 50-59.

5. Comparative assessment of data obtained using empirical models for path loss predictions in a university campus environment

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