Bio-inspired algorithm optimization of neural network for the prediction of Dubai crude oil price
Previous studies proposed several bio-inspired algorithms for the optimization of Neural Network (NN) to avoid local minima and to improve accuracy and convergence speed. To advance the performance of NN, a new bio-inspired algorithm called Flower Pollination Algorithm (FPA) is used to optimize t...
| Main Authors: | , , , , , , , |
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| Format: | Book Chapter |
| Language: | English English |
| Published: |
Springer Nature Singapore
2019
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/74275/ http://irep.iium.edu.my/74275/ http://irep.iium.edu.my/74275/ http://irep.iium.edu.my/74275/7/74275_Estimation%20of%20Middle-East%20Oil%20Consumption_scopus.pdf http://irep.iium.edu.my/74275/12/74275_Bio-inspired%20algorithm%20optimization.pdf |
| Summary: | Previous studies proposed several bio-inspired algorithms for the optimization
of Neural Network (NN) to avoid local minima and to improve accuracy
and convergence speed. To advance the performance of NN, a new bio-inspired algorithm
called Flower Pollination Algorithm (FPA) is used to optimize the weights and
bias of NN due to its ability to explore very large search space and frequent chosen
of similar solution. The FPA optimized NN (FPNN) was applied to build a
model for the prediction of Dubai crude oil price unlike previous studies that mainly
focus on theWest Texas Intermediate and Brent crude oil price benchmarks. Results |
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