A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm

• Main Authors: Haruna, Chiroma, Khan, Abdullah, Abubakar, Adamu, Saudi, Younes, Hamza, Mukhtar Fatihu, Shuiba, Liyana, Gital, Abdulsalam, Herawan, Tutut
• Format: Article
• Language: English; English
• Published: Elsevier 2016
• Subjects: QA76 Computer software
• Online Access: http://irep.iium.edu.my/51477/1/A_new_approach_for_forecasting_OPEC_petroleum_consumption_based_on_neural_network_train_by_using_flowerpollination_algorithm.pdf; http://irep.iium.edu.my/51477/4/51477_A_new_approach_for_forecasting_OPEC_petroleum_SCOPUS.pdf; http://irep.iium.edu.my/51477/; http://www.sciencedirect.com/science/article/pii/S1568494616303180
• Institution: Universiti Islam Antarabangsa Malaysia

Petroleum is the live wire of modern technology and its operations, with economic development being positively linked to petroleum consumption. Many meta-heuristic algorithms have been proposed in literature for the optimization of Neural Network (NN) to build a forecasting model. In this paper, as...