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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| Main Authors: | , , |
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| Format: | Article |
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Trans Tech Publications Inc.
2015
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| Subjects: | |
| Online Access: | http://repo.uum.edu.my/16490/ http://doi.org/10.4028/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. |
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