HSIC bottleneck based distributed deep learning model for load forecasting in smart grid with a comprehensive survey
Load forecasting is a vital part of smart grids for predicting the required electrical power
using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the …
using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the …
Multi-agent task planning and resource apportionment in a smart grid
Nowadays, in different fields, tremendous attention is received by the Multi-agent systems for
complex problem solutions with smaller task subdivision. Multiple inputs are utilized, eg …
complex problem solutions with smaller task subdivision. Multiple inputs are utilized, eg …
[HTML][HTML] 3D relative directions based evolutionary computation for UAV-to-UAV interaction in swarm intelligence enabled decentralized networks
Swarm intelligence (SI) is the collective behavior of several intelligent agents (IAs), and
unmanned aerial vehicles (UAV) or drones are widely used as IA in SI, of which UAV-based …
unmanned aerial vehicles (UAV) or drones are widely used as IA in SI, of which UAV-based …
Relative direction: location path providing method for allied intelligent agent
The most widely recognized relative directions are left, right, forward and backward. This
paper has presented a computational technique for tracking location by learning relative …
paper has presented a computational technique for tracking location by learning relative …
[PDF][PDF] HSIC bottleneck based distributed deep learning model for load forecasting in smart grid with a comprehensive survey
Load forecasting is a vital part of smart grids for predicting the required electrical power
using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the …
using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the …