The usage of IoT-based smart meter in electric power consumption shows a significant role
in helping the users to manage and control their electric power consumption. It produces …

Forecasting the electricity load provides its future trends, consumption patterns and its
usage. There is no proper strategy to monitor the energy consumption and generation; and …

Abstract Machine learning approaches have diverse applications in forecasting electrical
energy consumption using smart meter data. Various classification techniques and …

The ongoing upsurge of deep learning and artificial intelligence methodologies manifest
incredible accomplishment in a broad scope of assessing issues in different industries …

With the growth of forecasting models, energy forecasting is used for better planning,
operation, and management in the electric grid. It is important to improve the accuracy of …

A smart city is a sustainable and effective metropolitan hub, that offers its residents high
excellence of life through appropriate resource management. Energy management is …

Electrical load forecasting provides knowledge about future consumption and generation of
electricity. There is a high level of fluctuation behavior between energy generation and …

In this article, a new hybrid deep learning (DL) algorithm is developed to make a computer-
assisted forecasting energy management (EM) system. Applying the Copula function, the …

Short-term load prediction at the district-level is essential for feeders, substations,
consumers and transformers starts from 1-h to one-week ahead. Though, the critical problem …

Electricity is one of the critical role players to build an economy. Electricity consumption and
generation can affect the overall policy of the country. Such importance opens an area for …