An Application of Grey Wolf Optimizer for Commodity Price Forecasting

Over the recent decades, there are many nature inspired optimization algorithms have been introduced. In this study, a newly algorithm namely Grey Wolf Optimizer (GWO) is employed for gasoline price forecasting. The performance of GWO is compared against the results produced by Artificial Bee Colony...

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Bibliographic Details
Main Authors: Zuriani, Mustaffa, M. H., Sulaiman, Yuhani, Yusof
Format: Article
Language:English
Published: Trans Tech Publication 2015
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Online Access:http://umpir.ump.edu.my/id/eprint/10364/1/An%20Application%20of%20Grey%20Wolf%20Optimizer%20for%20Commodity%20Price%20Forecasting.pdf
http://umpir.ump.edu.my/id/eprint/10364/
http://www.scientific.net/AMM.785.473
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Summary:Over the recent decades, there are many nature inspired optimization algorithms have been introduced. In this study, a newly algorithm namely Grey Wolf Optimizer (GWO) is employed for gasoline price forecasting. The performance of GWO is compared against the results produced by Artificial Bee Colony (ABC) algorithm and Differential Evolution (DE) algorithm. Measured based on Mean Absolute Percentage Error (MAPE) and prediction accuracy, the GWO is proven to produce significantly better results as compared to the identified algorithms.