Affiliations: [a] Department of Industrial Engineering, Istanbul University-Cerrahpasa, Avcilar, Istanbul, Turkey
| [b] Department of Mechanical Engineering, Istanbul University-Cerrahpasa, Avcilar, Istanbul, Turkey
| [c] Department of Management Engineering, Faculty of Management, Istanbul Technical University, Macka, Istanbul, Turkey
Correspondence:
[*]
Corresponding author. Ceyda Tanyolaç Bilgiç, Department of Industrial Engineering, Istanbul University-Cerrahpasa, 34320, Avcilar, Istanbul, Turkey. E-mail: ceydatan@iuc.edu.tr.
Abstract: It is significant that the forecasting models give the closest result to the true value. Forecasting models are widespread in the literature. The grey model gives successful results with limited data. The existing Triangular Fuzzy Grey Model (TFGM (1,1)) in the literature is very useful in that it gives the maximum, minimum and average value directly in the data. A novel combined forecasting model named, Moth Flame Optimization Algorithm optimization of Triangular Fuzzy Grey Model, MFO-TFGM (1,1), is presented in this study. The existing TFGM (1,1) model parameters are optimized by a new nature- inspired heuristic algorithm named Moth-Flame Optimization algorithm which is inspired by the moths flying path. Unlike the studies in the literature, in order to improve the forecasting accuracy, six parameters (λL, λM, λR, α, β and γ) were optimized. After the steps of the model is presented, a forecasting implementation has been made with the proposed model. Turkey’s hourly electricity consumption data is utilized to show the success of the prediction model. Prediction results of proposed model is compared with TFGM (1,1). MFO-TFGM (1,1) performs higher forecasting accuracy.
