A proposed method using neural network for electricity price prediction base on genetic algorithm. (March 2019)

• Record Type: Journal Article
• Authors: Sobri Sungkar, Muchamad; Somantri, Oman; Taufik Qurohman, M; Romadani, ; Kurnia Bakti, Very; Rahim, Robbi
• Is Part Of: Journal of physics. Volume 1175(2019)
• Publication Date: 2019-03
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1175/1/012063
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In predicting the electricity price, neural network is used as an applied model. To implement the neural network there are several parameters that we must determine such as learning rate and momentum, the problem is there is no standard guideline in determining the parameters to be used in this method, so that the experimental method is used. Therefore, we need method that can solve these problems, so parameters determination can be more optimal. The solution that can be applied is using genetic algorithm on neural network by optimizing the value of learning rate, momentum and training cycles parameter. The expected result is it can accelerate the process in getting the appropriate and optimal parameter values on neural network, so it can increase the accuracy of the prediction in predicting electricity price.