This paper presents a hybrid approach for clustering based on particle swarm optimization (PSO) and bacteria foraging algorithms (BFA). The new method AutoCPB (Auto-Clustering based on particle bacterial foraging) makes use of autonomous agents whose primary objective is to cluster chunks of data by using simplistic collaboration. Inspired by the advances in clustering using particle swarm opti...

This project bestows optimal sizing and placement of FACTS device, which is achieved by the searching method of bacteria foraging algorithm (BFA) with optimal sizing of FACTS device. Static Var Compensator (SVC) is one of the FACTS devices, utilized for progress of voltage profile and loss minimization. The precise strategy of SVC offers the real power loss minimization with increase of voltage...

this paper proposes a novel hybrid algorithm namely apso-bfo which combines merits of bacterial foraging optimization (bfo) algorithm and adaptive particle swarm optimization (apso) algorithm to determine the optimal pid parameters for control of nonlinear systems. to balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

This paper proposes the exchange market algorithm (EMA) to solve the combined economic and emission dispatch (CEED) problems in thermal power plants. The EMA is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. Existence of two seeking operators in EMA provides a high ability in exploiting global optimum point. In order to show the capabilities ...

In this paper, a hybrid approach involving neural network (NN)-Bacterial Foraging Algorithm (BFA) is proposed for Automatic Generation Control of power system. The proposed algorithm is implemented to tune PID controller and the stability of interconnected system is improved. The feed forward Neural Network is to ensure the distribution of stochastic value with respective to chemotactic step si...

The roll of consumption energy forecasting is very important to make planning time-horizon strategy, and mitigate a great management. As result, improving the sustainability energy, creating clean environment. Aiming develop in different time horizons, this work gives results new hybrid method, which combine deep echo state network (DeepESN), with Binary genetic algorithm (BGA). DeepESN an exte...

In this paper, the problem of finding the optimal topological configuration of a deregulated distribution network is considered. The new features of this paper are proposing a multiobjective function and its application on deregulated distribution networks for finding the optimal configuration. The multi-objective function will be defined for minimizing total Energy Supply Costs (ESC) and energ...

this paper proposes the exchange market algorithm (ema) to solve the combined economic and emission dispatch (ceed) problems in thermal power plants. the ema is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. existence of two seeking operators in ema provides a high ability in exploiting global optimum point. in order to show the capabilities ...