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In IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society (October 2012), pp. 1217-1222, doi:10.1109/iecon.2012.6388597 Key: citeulike:12054499
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Energy management for residential homes and offices require the prediction of the usage(s) or service request(s) of different appliances present in the house. The hardware requirement is more simplified and practical if the task is only based on energy consumption data and no other sensors are used. The proposed model tries to formalize such an approach using a time-series based multi-label classifier which takes into account correlation between different appliances among other factors. In this work, prediction results are shown for 1-hour in the future but this approach can be extended to predict more hours in the future as per the requirement(with restrictions). The learned models and decision tree showing the important factors in the input information is also discussed.
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