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              <text>Exact prediction and consumption of residential electricity power cost hours, daily, weekly, monthly using ant, ML and DL techniques /</text>
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              <text>Patent Number: 202241055650, Applicant: Dr. S Perumal.&#13;
This research describes an unique method for predicting energy consumption based on deep neural networks that can accurately estimate the hourly energy consumption profile of a residential building one day in advance, taking occupancy into account. Providers of energy and utilities can determine the most efficient generation schedule if they have an accurate evaluation of the quantity of energy utilised by houses. A comprehensive review of a number of criteria was undertaken in order to initiate an investigation into the various energy estimation techniques that employ machine learning.</text>
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              <text>Das, Tapas.</text>
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              <text>&lt;a href="https://drive.google.com/file/d/1KPTEa0TJm_LjmgCTWBatLyR0YOMdN7Jk/view" target="_blank" title="Exact prediction and consumption of residential electricity power cost hours, daily, weekly, monthly using ant, ML and DL techniques /" rel="noreferrer noopener"&gt;https://drive.google.com/file/d/1KPTEa0TJm_LjmgCTWBatLyR0YOMdN7Jk/view&lt;/a&gt;</text>
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