Influence of climatic variables on wireless: case study Base-Station Receiver

Authors

  • Rodolfo Najarro Quintero Universidad Técnica Estatal de Quevedo
  • Eduardo Samaniego Mena Universidad Técnica Estatal de Quevedo
  • Freddy Fares Vargas Universidad Técnica Estatal de Quevedo
  • Amilkar Puris Cáceres Universidad Técnica Estatal de Quevedo

DOI:

https://doi.org/10.29019/enfoqueute.v7n4.116

Keywords:

Supervised classification, climatology, signal attenuation, fuzzy ruler

Abstract

The development of this research is done with the aim of finding the relationship betweenweather conditions and the loss of wireless connection. The data were obtained by ameteorological center of the area and a telecommunications company that operates in the sameplace. We studied different models based on fuzzy logic due to the easy interpretation the easyinterpretation of the rules and data management. We used the Weka application that providestools for pre-processing of data and Keel software tool for data classification. Nine classifiersbased on fuzzy rules were applied, where the Furia-C was that better results obtained in orderto quality and quantity of rules. In this scenario, a preprocessing of data were computed, wheresome techniques to improve the information was performed. Some of the obtained rulerscorroborate the influence of heavy rain over the loss of the signal, but other relationships thatincorporate new knowledge in the area, such as dew point and the average relative humidityappear.

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References

Bartczuk, L., Przybyl, A., & Cpalka, K. (2016). A new approach to nonlinear modelling of dynamic systems based on fuzzy rules. International Journal of Applied Mathematics and Computer Science, 26(3), 603-621.
Del Jesús, M. J., Hoffmann, F., Navascués, L. J., & Sánchez, L. (2004). Induction of fuzzy-rule-based classifiers with evolutionary boosting algorithms. IEEE Transactions on Fuzzy Systems, 12(3), 296-308.
Fermín, J. R., & Simancas, M. (2010). Pronóstico de la atenuación por lluvia en las comunicaciones satelitales mediante métodos de regresión. Télématique: Revista Electrónica de Estudios Telemáticos, 9(3), 23-35.
Gao, Q., & He, N. B. (2016). Study on Fuzzy Classifier Based on Genetic Algorithm Optimization. In Proceedings of the 5th International Conference on Electrical Engineering and Automatic Control (pp. 725-731). Springer Berlin Heidelberg.
González, A., Pérez, R., Caises, Y., & Leyva, E. (2012). An efficient inductive genetic learning algorithm for fuzzy relational rules. International Journal of Computational Intelligence Systems, 5(2), 212-230.
Hühn, J., & Hüllermeier, E. (2009). FURIA: an algorithm for unordered fuzzy rule induction. Data Mining and Knowledge Discovery, 19(3), 293-319.
Mansoori, E. G., Zolghadri, M. J., & Katebi, S. D. (2008). SGERD: A steady-state genetic algorithm for extracting fuzzy classification rules from data. IEEE Transactions on Fuzzy Systems, 16(4), 1061-1071.
Moncada, D. (2006). Efectos de Atenuación por Lluvia en los Medios de Transmisión entre Sistemas Satelitales y Estaciones Terrestres. Trabajo de grado para optar al Título de Magíster en Telemática. Universidad Rafael Belloso Chacín. Maracaibo, Venezuela.
Murcia, C., Bonilla, G., & Melgarejo, M. (2014). Fuzzy Classifiers Tuning Through an Adaptive Memetic Algorithm. IEEE Latin America Transactions, 12(2), 197-204.
Sánchez, L., Couso, I., & Corrales, J. A. (2001). Combining GP operators with SA search to evolve fuzzy rule based classifiers. Information Sciences, 136(1), 175-191.
Sánchez, L., Couso, I., & Corrales, J. A. (2001). Combining GP operators with SA search to evolve fuzzy rule based classifiers. Information Sciences, 136(1), 175-191.
Sudha, M. (2017). Intelligent decision support system based on rough set and fuzzy logic approach for efficacious precipitation forecast. Decision Science Letters, 6(1), 95-106.
Xie, Z., Jiang, L., Ye, T., & Li, X. (2015). A synthetic minority oversampling method based on local densities in low-dimensional space for imbalanced learning. In International Conference on Database Systems for Advanced Applications (pp. 3-18

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Published

2016-12-15

How to Cite

Najarro Quintero, R., Samaniego Mena, E., Fares Vargas, F., & Puris Cáceres, A. (2016). Influence of climatic variables on wireless: case study Base-Station Receiver. Enfoque UTE, 7(4), pp. 86 – 95. https://doi.org/10.29019/enfoqueute.v7n4.116

Issue

Vol. 7 No. 4 (2016)

Section

Miscellaneous

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