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All Journal International Journal of Electrical and Computer Engineering MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) INFORMAL: Informatics Journal INTEGRITAS : Jurnal Pengabdian TEKIBA : Jurnal Teknologi dan Pengabdian Masyarakat Room of Civil Society Development Proceeding International Conference Of Innovation Science, Technology, Education, Children And Health Proceeding International Conference Of Innovation Science, Technology, Education, Children And Health Room of Civil Social Development
Gayatri Dwi Santika
Program Studi Informatika, Universitas Jember
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Other

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Journal : International Journal of Electrical and Computer Engineering

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Rule Optimization of Fuzzy Inference System Sugeno using Evolution Strategy for Electricity Consumption Forecasting Gayatri Dwi Santika; Wayan Firdaus Mahmudy; Agus Naba
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 4: August 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (849.029 KB) | DOI: 10.11591/ijece.v7i4.pp2241-2252

Abstract

The need for accurate load forecasts will increase in the future because of the dramatic changes occurring in the electricity consumption. Sugeno fuzzy inference system (FIS) can be used for short-term load forecasting. However, challenges in the electrical load forecasting are the data used the data trend. Therefore, it is difficult to develop appropriate fuzzy rules for Sugeno FIS. This paper proposes Evolution Strategy method to determine appropriate rules for Sugeno FIS that have minimum forecasting error. Root Mean Square Error (RMSE) is used to evaluate the goodness of the forecasting result. The numerical experiments show the effectiveness of the proposed optimized Sugeno FIS for several test-case problems. The optimized Sugeno FIS produce lower RMSE comparable to those achieved by other well-known method in the literature.
Co-Authors Agus Naba Allysa, Pupud Deanira Amalia, Karina Nine Bayhaqqi Bayhaqqi Farchanulhady, Reefadhinta Ubaidillah Firmansyah, Diksy Media Furqon, Muhammad Ariful Hidayat, Muhamad Arief mahmudy, wayan f Nugraha, Tri Agustina retnani, windy eka yulia S, M Zaki Saiful Bukhori Sari, Nadia Roosmalita Satrio Thoriq Shenny Syavira, Anintya Alisya Valiant Shabri Rabbani Wayan Firdaus Mahmudy