Comparative Analysis Between Feedforward Neural Network and CNN-LSTM Neural Network To Predict Household Electrical Energy Consumption
Author:
Affiliation:
1. Florida International University,Electrical And Computer Engineering,Miami,USA
2. Vellore Institute of Technology,School of Computing Science,Bhopal,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10252163/10252090/10253452.pdf?arnumber=10253452
Reference23 articles.
1. A novel hybridization of artificial neural networks and ARIMA models for time series forecasting
2. Prediction of energy consumption in buildings by system identification
3. Predicting the Household Power Consumption Using CNN-LSTM Hybrid Networks
4. Advancements and challenges in machine learning: A comprehensive review of models, libraries, applications, and algorithms;tufail;Electronics,2023
5. Hybrid Technique for the Analysis of Non-Linear and Non-Stationary Signals focused on Power Quality
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