2012 ©
             Publication
Journal Publication
Title of Article Cultural Algorithm Initializes Weights of Neural Network Model for Annual Electricity Consumption Prediction 
Date of Acceptance 13 June 2020 
Journal
     Title of Journal International Journal of Advanced Computer Science and Applications  
     Standard  
     Institute of Journal The Science and Information (SAI) Organization 
     ISBN/ISSN  
     Volume 11 
     Issue
     Month June
     Year of Publication 2020 
     Page 101 - 110 
     Abstract The accurate prediction of annual electricity consumption is crucial in managing energy operations. The neural network (NN) has achieved a lot of achievements in annual electricity consumption prediction due to its universal approximation property. However, the well-known back-propagation (BP) algorithms for training NN has easily got stuck in local optima. In this paper, we study the weights initialization of NN for the prediction of annual electricity consumption using the Cultural algorithm (CA), and the proposed algorithm is named as NN-CA. The NN-CA was compared to the weights initialization using the other six metaheuristic algorithms as well as the BP. The experiments were conducted on the annual electricity consumption datasets taken from 21 countries. The experimental results showed that the proposed NN-CA achieved more productive and better prediction accuracy than other competitors. This result indicates the possible consequences of the proposed NN-CA in the application of annual electricity consumption prediction. 
     Keyword Neural network, Weights initialization, Metaheuristic algorithm, Cultural algorithm, Annual electricity consumption prediction. 
Author
607020023-0 Miss GAWALEE PHATAI [Main Author]
College of Computing Doctoral Degree

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Level of Publication นานาชาติ 
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