Citation Impact
Citing Papers
A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications
2015 Standout
An AIS-ACO Hybrid Approach for Multi-Objective Distribution System Reconfiguration
2007
Distribution system minimum loss reconfiguration in the Hyper-Cube Ant Colony Optimization framework
2008
AC-microgrids versus DC-microgrids with distributed energy resources: A review
2013 Standout
Overview and literature survey of fuzzy set theory in power systems
1995
Reinforcement learning for building controls: The opportunities and challenges
2020 Standout
Recent Philosophies of Automatic Generation Control Strategies in Power Systems
2005 Standout
An effective Power Quality classifier using Wavelet Transform and Support Vector Machines
2015
An Efficient Codification to Solve Distribution Network Reconfiguration for Loss Reduction Problem
2008
Machine Learning and Deep Learning in smart manufacturing: The Smart Grid paradigm
2021 Standout
Multi-objective particle swarm optimization based on fuzzy-Pareto-dominance for possibilistic planning of electrical distribution systems incorporating distributed generation
2012
Adapted ant colony optimization for efficient reconfiguration of balanced and unbalanced distribution systems for loss minimization
2011 Standout
Optimum design of hybrid renewable energy systems: Overview of different approaches
2012
Works of Nelson Kagan being referenced
Design model for electrical distribution systems considering renewable, conventional and energy storage units
1992
Electrical power distribution systems planning using fuzzy mathematical programming
1994
Fast Reconfiguration of Distribution Systems Considering Loss Minimization
2005
Automatic power quality disturbance classification using wavelet, support vector machine and artificial neural network
2009
A Benders' decomposition approach to the multi-objective distribution planning problem
1993
Intelligent Decision-Making for Smart Home Energy Management
2014
Reconfiguration of distribution networks to minimize loss and disruption costs using genetic algorithms
2009