Muhammad, Sadli and Fajriana, Fajriana and Wahyu, Fuadi and Ermatita, Ermatita and Iwan, Pahendra (2022) Similarity - Electrical peak load forecasting using long short term memory and support vector machine. Turnitin Universitas Sriwijaya. (Submitted)
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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 |
|---|---|
| Uncontrolled Keywords: | LSTM, SVM |
| Subjects: | Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA75.5 Mathematics--Periodicals. Computer engineering. Computer science |
| Divisions: | 09-Faculty of Computer Science > 57201-Information Systems (S1) |
| Depositing User: | Dr Ermatita zuhairi |
| Date Deposited: | 15 Mar 2022 07:05 |
| Last Modified: | 15 Mar 2022 07:05 |
| URI: | http://repository.unsri.ac.id/id/eprint/66094 |
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