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/74275/7/74275_Estimation%20of%20Middle-East%20Oil%20Consumption_scopus.pdf http://irep.iium.edu.my/74275/12/74275_Bio-inspired%20algorithm%20optimization.pdf |
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| author | Haruna, Chiroma Abdul-Kareem, Sameem Saadi, Younes Khan, Abdullah Abubakar, Adamu Abdullahi Muaz, Sanah Ya’u Gital, Abdulsalam Mohd Shuib, Nor Liyana |
| author_facet | Haruna, Chiroma Abdul-Kareem, Sameem Saadi, Younes Khan, Abdullah Abubakar, Adamu Abdullahi Muaz, Sanah Ya’u Gital, Abdulsalam Mohd Shuib, Nor Liyana |
| author_sort | Haruna, Chiroma |
| building | IIUM Repository |
| collection | Online Access |
| description | 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 |
| first_indexed | 2025-11-14T17:32:53Z |
| format | Book Chapter |
| id | iium-74275 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:32:53Z |
| publishDate | 2019 |
| publisher | Springer Nature Singapore |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-742752020-01-29T07:41:26Z http://irep.iium.edu.my/74275/ Bio-inspired algorithm optimization of neural network for the prediction of Dubai crude oil price Haruna, Chiroma Abdul-Kareem, Sameem Saadi, Younes Khan, Abdullah Abubakar, Adamu Abdullahi Muaz, Sanah Ya’u Gital, Abdulsalam Mohd Shuib, Nor Liyana Q350 Information theory 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 Springer Nature Singapore 2019 Book Chapter PeerReviewed application/pdf en http://irep.iium.edu.my/74275/7/74275_Estimation%20of%20Middle-East%20Oil%20Consumption_scopus.pdf application/pdf en http://irep.iium.edu.my/74275/12/74275_Bio-inspired%20algorithm%20optimization.pdf Haruna, Chiroma and Abdul-Kareem, Sameem and Saadi, Younes and Khan, Abdullah and Abubakar, Adamu and Abdullahi Muaz, Sanah and Ya’u Gital, Abdulsalam and Mohd Shuib, Nor Liyana (2019) Bio-inspired algorithm optimization of neural network for the prediction of Dubai crude oil price. In: Lecture Notes in Electrical Engineering. Lecture Notes in Electrical Engineering, 520 (https://doi.org/10.1007/978-981-13-1799-6_17). Springer Nature Singapore, Singapore, pp. 151-162. ISBN 978-3-030-17794-2 https://link.springer.com/chapter/10.1007%2F978-981-13-1799-6_16 https://doi.org/10.3991/ijim.v13i01.7037 |
| spellingShingle | Q350 Information theory Haruna, Chiroma Abdul-Kareem, Sameem Saadi, Younes Khan, Abdullah Abubakar, Adamu Abdullahi Muaz, Sanah Ya’u Gital, Abdulsalam Mohd Shuib, Nor Liyana Bio-inspired algorithm optimization of neural network for the prediction of Dubai crude oil price |
| title | Bio-inspired algorithm optimization of neural network for the prediction of Dubai crude oil price |
| title_full | Bio-inspired algorithm optimization of neural network for the prediction of Dubai crude oil price |
| title_fullStr | Bio-inspired algorithm optimization of neural network for the prediction of Dubai crude oil price |
| title_full_unstemmed | Bio-inspired algorithm optimization of neural network for the prediction of Dubai crude oil price |
| title_short | Bio-inspired algorithm optimization of neural network for the prediction of Dubai crude oil price |
| title_sort | bio-inspired algorithm optimization of neural network for the prediction of dubai crude oil price |
| topic | Q350 Information theory |
| url | 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 |