Tag Archives: fuzzy set.

WEATHER EVENTS FORECASTING IN KOTA KINABALU USING A FUZZY RULE-BASED SYSTEM

Posted on by

Suzelawati Zenian and Amirah Ramizah Bibi Abdul Rasheed

Mathematics with Computer Graphics, Faculty of Science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia.

ABSTRACT. A weather forecast is a prediction of weather phenomena in the future by collecting as much data as possible. Major worldwide climate studies include the breakthrough and interpretation of complicated weather patterns in order to successfully forecast varied weather events. It is quite complex to screen so many parameters from several factors to discover precise weather conditions. In this paper, a fuzzy rule-based system (FRBS) is applied for weather forecasting in Kota Kinabalu. There are 234 fuzzy rules being developed as the FRBS are constructed along and successfully implemented in MATLAB. Based on the results, the comparison between actual and forecast data shows moderate precision as the accuracy level is higher than the level of error analysis.

KEYWORDS. Weather events, fuzzy rule-based system, forecasting, fuzzy set.

REFERENCES

  • Agboola, A, & Gabriel. 2013.Development of a Fuzzy Logic Based Rainfall Prediction Model. International Journal of Engineering and Technology, vol. 3, no. 4, 427–435.
    Awan, M. S. K. & Awais, M. M. 2011. Predicting Weather Events Using Fuzzy Rule-Based System. Applied Soft Computing, 11(1), 56–63.
  • Cihan, P. Fuzzy Rule-Based System for Predicting Daily Case in COVID-19 Outbreak . 2020. 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), Istanbul, Turkey, 2020, pp. 1-4, doi: 10.1109/ISMSIT50672.2020.9254714.
  • Hemayatkar, N., Khalili-Damghani, K., Didehkhani, H., & Samiee, R. 2018. Developing a fuzzy inference system to devise proper business strategies: A study on carpet industry. Journal of Industrial Engineering International, 15(3), 529–544.
  • Khatua, A., Jana, S., & Kar, T. K. 2020. A fuzzy rule-based model to assess the effects of global warming, pollution and harvesting on the production of Hilsa fishes. Ecological Informatics, 57(February), 101070. 1-7.
  • Malaysia Meteorological Department (MMD). 2016. General Climate of Malaysia (http://www.met.gov.my).
  • Mojiol, A. R. 2006. Ecological Landuse Planning and Sustainable Management of Urban and Sub-urban Green Areas in Kota Kinabalu, Malaysia. Goettingen: Cuvillier Verlag.
  • Moler, C., & Little, J. 2020. A history of MATLAB. Proceedings of the ACM on Programming Languages, 4(HOPL), 1–67.
  • Ross, T. J. 2010. Fuzzy Logic with Engineering Applications, 3rd Ed. John Wiley & Sons, Ltd.
  • Sharma, M., Mathew, L., & Chatterji, S. 2014. Weather Forecasting using Soft Computing and Statistical Techniques. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 3(7), 11285–11290.
  • Zadeh, L.A. 1975. The Concept of a Linguistic Variable and Its Application to Approximate Reasoning-III. Information Sciences, vol. 9, no. 1, 43–80.

Download Full Paper Here (Right-Click and Save As)

ACKNOWLEDGEMENT
The authors would like to express their appreciation and gratitude to the Research Management Centre, Universiti Malaysia Sabah for the continued support