Korespondensi " Electrical peak load forecasting using long short term memory and support vector machine

Muhammad Sadli, Muhammad Sadli and Fajriana, Fajriana and Wahyu Fuadi, Wahyu Fuadi and Ermatita, Ermatita and Iwan Pahendra, Iwan Pahendra (2020) Korespondensi " Electrical peak load forecasting using long short term memory and support vector machine. IOP Conference Series: Materials Science and Engineering.

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Official URL: https://iopscience.iop.org/article/10.1088/1757-89...

Abstract

Abstract Electrical load forecasting is usually a univariate time series forecasting problem. In this case, we use the machine learning approach based on Long Short Term Memory and Support Vector Machine. Accurate the peak electric load forecasting. The time series or data set of the peak electric load recorded from the Substation system in Lhoksumewe, Indonesia. The main aim of this paper to predict and evaluate the performance of peak electric load at the substation for six months. The results obtained in the study, the LSTM and SVM are proving useful for peak electrical load forecasting. The resulting point both of machine learning technique based on LSTM and SVM are a possibility for analysis data for such purposes.

Item Type: Other
Subjects: T Technology & Engineering > TI Informatics, Information System
Divisions: Faculty of Engineering > Department of Information System
Depositing User: Dr. Fajriana S.Si, M.Si
Date Deposited: 03 May 2023 01:34
Last Modified: 03 May 2023 01:34
URI: http://repository.unimal.ac.id/id/eprint/7631

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