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Showing 1 to 3 of 3 for “"Electrical Load Forecasting"”.

  1. A Deep Learning-based Dynamic Demand Response Framework

    … is to shut down the operation of pre-selected electrical equipment i.e., heating, ventilation and air conditioning (HVAC) and lights to reduce power consumption. This approach, however, is not optimal and does not take into consideration any user preference. Furthermore, this does not provide …

    vt Repository record for A Deep Learning-based Dynamic Demand Response Framework (opens in a new tab)

  2. Forecasting Energy Consumption using Sequence to Sequence Attention models

    … created possibilities for sensor based energy forecasting. Machine learning algorithms commonly used for energy forecasting, such as FeedForward Neural Networks, are not well-suited for interpreting the time dimensionality of a signal. Consequently, this thesis applies Sequence-to-Sequence …

    uwo Repository record for Forecasting Energy Consumption using Sequence to Sequence Attention models (opens in a new tab)

  3. The use of artificial intelligence techniques for power analysis

    … Artificial Neural Networks is demonstrated for Electrical Load Forecasting and the use of Self Organising Maps is explored for classifying Power System digital fault records. The background of the optimisation process carried out in this thesis is given and an introduction to the method applied, …

    city-london Repository record for The use of artificial intelligence techniques for power analysis (opens in a new tab)