Short-Term Energy Consumption Forecasting Analysis Using Different Optimization and Activation Functions with Deep Learning Models

Short-Term Energy Consumption Forecasting Analysis Using Different Optimization and Activation Functions with Deep Learning Models

Modelling events that change over time is one of the most difficult problems in data analysis. Forecasting of time-varying electric power values is also an important problem in data analysis. Regression methods, machine learning, and deep learning methods are used to learn different patterns from da...

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Bibliographic Details
Main Authors: Mehmet Tahir Ucar, Asim Kaygusuz
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Applied Sciences
Subjects:
deep learning models
electricity consumption prediction
exploratory data analysis (EDA)
long short-term memory (LSTM)
gated recurrent unit (GRU)
simple recurrent neural networks (Simple RNN)
Online Access:https://www.mdpi.com/2076-3417/15/12/6839
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