Fault diagnosis of induction motor anomalies is vital for achieving industry safety. This paper proposes a new hybrid Machine Learning methodology induction-motor fault detection. Some the parameters such as stator currents and vibration signals provide great deal information about motor’s conditions. Therefore, these were selected to test proposed model. The was assessed in laboratory under he...

This paper presents a new optimization algorithm to design an optimal proportional, integral, derivative (PID) controller in hydro-turbine generator governor for damping output frequency oscillations. In this research, we utilize a stochastic and optimal based PID controller to control frequency-response of the hydro turbine. The proposed algorithm is employed to design an optimal PID controlle...

This paper presents a new optimization algorithm to design an optimal proportional, integral, derivative (PID) controller in hydro-turbine generator governor for damping output frequency oscillations. In this research, we utilize a stochastic and optimal based PID controller to control frequency-response of the hydro turbine. The proposed algorithm is employed to design an optimal PID controlle...

a new powerful optimization algorithm inspired from colonizing weeds is utilized to solve the well-known quadratic assignment problem (qap) which is of application in a large number of practical areas such as plant layout, machinery layout and so on. a set of reference numerical problems from qaplib is taken in order to evaluate the efficiency of the algorithm compared with the previous ones wh...

So many studies have been done in order to execute all the tasks in real-time scheduler systems. However, different researcher are tried to tackle overload situation in real-time systems by using swarm algorithm. These studies have been categorized based on the various parameters which are important in real-time systems. As an instance, system cost, processor waiting time, number of tasks, bala...

Invasive Weed Optimization is a recently proposed population based meta-heuristic that mimics the colonizing action of weeds. In this article, an improvement to the classical algorithm has been proposed by introducing a constriction factor in the seed dispersal stage. Temporal Difference Q-Learning has been employed to adapt this parameter for different population members through the successive...

In this paper, an artificial-based optimizes and analysis of an optimal proportional, integral, derivative (PID) controller is introduced for a hydro-turbine generator governor. The main purpose, optimization PID controller parameters of hydro-turbine connected to the network for damping output frequency oscillation. In The proposed approach, an optimal and evolutionary based proportional, inte...