A Weighted Subsethood Mamdani Fuzzy Rules Based System Rule Extraction (MFRB-WSBA) for Forecasting Electricity Load Demand - A Framework

Authors

  • Rosnalini Mansor School of Quantitative Sciences, UUM College of Arts and Sciences, Universiti Utara Malaysia, 06010, Sintok, Kedah, Malaysia
  • Maznah Mat Kasim School of Quantitative Sciences, UUM College of Arts and Sciences, Universiti Utara Malaysia, 06010, Sintok, Kedah, Malaysia
  • Mahmod Othman Department of Fundamental and Applied Sciences, Faculty of Science & Information Technology, Universiti Teknologi Petronas, 32610, Seri Iskandar, Perak, Malaysia

Keywords:

Fuzzy Rules, Forecasting, Electricity Load Demand,

Abstract

Fuzzy rules are very important elements that should be taken consideration seriously when applying any fuzzy system. This paper proposes the framework of Mamdani Fuzzy Rulebased System with Weighted Subsethood-based Algorithm (MFRBS-WSBA) for forecasting electricity load demand. Specifically, this paper proposed two frameworks: MFRBSWSBA and WSBA framework where the WSBA is embedded in MFRBS-WSBA (fourth step in MFRBS-WSBA). The objective of this paper is to show the fourth step in the MFRBS-WSBA framework which applied the new electricity load forecasting rule extraction by WSBA method. We apply the proposed WSBA framework in Malaysia electricity load demand data as a numerical example in this paper. These preliminary results show that the WSBA framework can be one of alternative methods to extract fuzzy rules for forecast electricity load demand where the proposed method provide a simple to interpret the fuzzy rules and also offer a new direction to interpret the fuzzy rules compared to classical fuzzy rules

References

Kumar, S., Narula, P., and Ahmed, T. Knowledge Extraction from Numerical Data for the Mamdani Type Fuzzy Systems : A BBO Approach. In Proceeding of the Innovative Practices in Management and Information Technology for Excellence. India. 2010. 1–10.

Abraham, A., and B. Nath., “A neuro-fuzzy approach for modellingelectricity demand in Victoria,” Applied Soft Computing. 1:127–138, 2001.

Sachdeva, S., and Verma, C. M. Load Forecasting using Fuzzy

Methods. In Proceeding of the Power System Technology and IEEE

Power India Conference. 2008. 1–4.

Cococcioni, M., Foschini, L., Lazzerini, B., and Marcelloni, F.,

“Complexity Reduction of Mamdani Fuzzy Systems through Multivalued Logic Minimization,” Proceeding in IEEE International

Conference on Systems, Man and Cybernetics. 1782–1787, 2008.

Rizwan, M., Kumar, D., and Kumar, R., “Fuzzy Logic Approach for Short Term Electrical Load Forecasting,” Electrical and Power

Engineering Frontier. 1(1): 8–12, 2012.

Jarrett, J. E., and Plouffe, J. S., “The Fuzzy Logic Method for Simpler Forecasting,” International Journal of Engineering Business

Management. 3(3):25–52, 2011.

Yazdania, A., Shariatib, S., and Yazdani-Chamzinic, A., “A risk

assessment model based on fuzzy logic for electricity distribution

system asset management,” Decision Science Letter. 3: 343–352, 2014.

Othman, M., Khalid, S., A., Abdullah, F., Hamzah, S. H. A., and Mahmud, K. R. K., “Hybrid Subjective Evaluation Method Using

Weighted Subsethood-based (WSBA ) Rule Generation Algorithm,”Journal of Arts, Science &Commerce. IV (1(1)): 46–54, 2013.

Othman, M., Saian, R., Nazri, M. N., Safiah, N., Kamal, A., and Liyana, N. Fuzzy Forecasting For Water Level of Flood Warning System in Perlis. Proceeding in International Symposium on Mathematical Sciences and Computing Research. 104–109, 2013.

Tiwari, S., Singh, V., and Kumar, R., “An Intelligent System For Forecasting Electric Load And Price,” International Journal of

Computer Sciences and Information Technologies. 6(3): 2121–2126,

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Published

2016-11-01

How to Cite

Mansor, R., Mat Kasim, M., & Othman, M. (2016). A Weighted Subsethood Mamdani Fuzzy Rules Based System Rule Extraction (MFRB-WSBA) for Forecasting Electricity Load Demand - A Framework. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 8(8), 97–102. Retrieved from https://jtec.utem.edu.my/jtec/article/view/1326

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