An Intelligent Approach for Performing Energy-Driven Classification of Buildings Utilizing Joint Electricity–Gas Patterns
نویسندگان
چکیده
Building type identification is an important task that may be used in confirming and verifying its legitimate operation. One of the main sources information over operation a building energy consumption, with analysis electricity patterns being at spotlight non-intrusive approach. However, are only source information, therefore, their imposes several restrictions. In this work, we introduce new approach energy-driven by adding one more beyond pattern utilized, namely gas consumption pattern. particular, propose intelligent jointly analyzes electricity–gas to provide hand. Our exploits synergism matrix profile data technique feed-forward artificial neural network. This has applicability waste elimination through implementation different efficiency solutions, as well optimization demand-side process management, safer reliable fault detection, validation real building. The obtained results demonstrate improvement identifying employing proposed for joint compared using patterns.
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ژورنال
عنوان ژورنال: Energies
سال: 2021
ISSN: ['1996-1073']
DOI: https://doi.org/10.3390/en14227465