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- W4313443600 abstract "According to the Electricity market, power consumption seems to be the actual energy demand which is made on the existing electricity supply. Recommendation systems play a significant role in Machine Learning and Artificial Intelligence. Recommender systems also plays a crucial role in majority of the industries. It uses various approaches in predicting user’s interest and provides relevant recommendations by using different filtering methods. This paper has a detailed survey on the recommender systems based on power consumption. Recommender systems provide different algorithms for an effective way of consuming power. Residential customers need to consume power efficiently and also can enjoy the alert system which reminds them of their monthly usage which inturn helps the customers to manage their electricity bill. In our proposed system the Power Limit Indicator system (PLIS) manages the usage of power for the individual residential customer. Residential customers of the PLIS are alerted based on the data of household appliances when their limit reaches the threshold. The PLIS outperforms other strategies which seem to provide a strong solution to power limit alert task." @default.
- W4313443600 created "2023-01-06" @default.
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- W4313443600 date "2023-01-01" @default.
- W4313443600 modified "2023-09-23" @default.
- W4313443600 title "A Survey on Power Consumption Indicator Using Machine Learning-Based Approach" @default.
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- W4313443600 doi "https://doi.org/10.1007/978-981-19-7169-3_21" @default.
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