Artificial Neural Network based Virtual Energy Meter
Dinesh Pansare, Tejashree Mule, Nikita Markad, Ashpana Shiralkar, Shashikant Bakre · 2021 International Conference on Emerging Smart Computing and Informatics (ESCI) · 2021
The concept of working of virtual meters has been emerged after evolution of IoT technology and cloud computing. In the meanwhile, the neural network models based on Python have also been emerged. In this paper, the concept of artificial neural network based virtual energy meter have been put forward. The logical AND gate based anomaly for virtual meter is presented. Secondly, using neural network based regression method, the novice method for power factor correction have been introduced. The computation of errors and adjustment of synaptic weights has been conducted using Python 3.0 version.