Data-driven computational algorithms for predicting electricity consumption missing values: A comparative study

Keyphrases

• Australia 50%
• Commercial User 50%
• Computational Algorithm 100%
• Copyright 50%
• Data Availability 50%
• Decision Tree 50%
• Decision Tree Regression 50%
• Electricity Consumption 100%
• Energy Usage 50%
• Linear Regression 100%
• Low-power Wide-area Network (LPWAN) 50%
• Machine Learning Models 100%
• MLP Model 50%
• Model-based Testing 50%
• Multilayer Perceptron 100%
• Prediction Algorithms 50%
• Predictive Machine Learning 50%
• Random Forest Regression 50%
• Random Tree 50%
• Regional Cities 50%
• Regression Linear 50%
• Training Model 50%
• Training Set 50%

Computer Science

• Data Availability 50%
• Decision Trees 100%
• Electricity Consumption 100%
• Individual User 50%
• Machine Learning 100%
• Multilayer Perceptron 100%
• Random Decision Forest 100%
• Training Model 50%