Real Power Loss Reduction by Extreme Learning Machine Based Leontodon Algorithm

In this paper Extreme Learning Machine based Leontodon Algorithm (ELMLA) has been applied for solving the Real Power loss reduction problem. Key objectives of are power reduction, Voltage stability enhancement and voltage deviation minimization. (LA) technique is an innovative swarm optimization algorithm. evolutionary procedure LA, eminence seeds engendered by rutted, outstanding will be reserved appraised, whereas deprived rejected. order to define whether a seed tremendous or not, algorithm with extreme learning machine projected in paper. Based on fitness values population segregated into Leontodons. Subsequently Leontodons apportioned corresponding labels as +1 if − 1 deprived), it considered training set, which built machine. Lastly, design categorize excellent deprived. Only selected take part evolution procedure. Legitimacy substantiated IEEE 30 bus system (with devoid L-index). Actual reached. Proportion actual augmented.