The python neuralnilm.RealApplianceSource is a module that provides a realistic dataset for training and testing neural network models in the field of non-intrusive load monitoring (NILM). It is specifically designed to simulate electrical power consumption data from various domestic appliances, such as refrigerators, air conditioners, and washing machines. This module helps researchers and developers to create more accurate and efficient NILM algorithms by facilitating the generation of realistic appliance-level power consumption data.
Python RealApplianceSource - 43 examples found. These are the top rated real world Python examples of neuralnilm.RealApplianceSource extracted from open source projects. You can rate examples to help us improve the quality of examples.