In this paper, a novel technique is developed by hybridizing Bacterial Foraging Optimization technique in conjunction with Particle Swarm Optimization and is applied to the expressions developed by M.Kara to calculate accurately the desired resonant frequency of rectangular microstrip antenna of any dimension and of any substrate thickness. Index Terms Bacterial Foraging Optimization (BFO), Par...

Data Mining is the process of extract useful information from the large data by using different mining techniques. Clustering and classification manage the large amount of data into different clusters according to their properties. Sometimes data arranged in clusters contain outliers that degrade the performance of the system. The outliers detected by K-Mean genetic algorithm also contain infor...

We show the emergence of Swarm Intelligence in physical robots. We transfer an optimization algorithm which is based on beeforaging behavior to a robotic swarm. In simulation this algorithm has already been shown to be more effective, scalable and adaptive than algorithms inspired by ant foraging. In addition to this advantage, bee-inspired foraging does not require (de-)centralized simulation ...

Bacterial foraging optimization algorithm (BFOA) has been widely accepted as a global optimization algorithm of current interest for distributed optimization and control. BFOA is inspired by the social foraging behavior of Escherichia coli. BFOA has already drawn the attention of researchers because of its efficiency in solving real-world optimization problems arising in several application dom...

We show the emergence of Swarm Intelligence in physical robots. We transfer an optimization algorithm which is based on beeforaging behavior to a robotic swarm. In simulation this algorithm has already been shown to be more effective, scalable and adaptive than algorithms inspired by ant foraging. In addition to this advantage, bee-inspired foraging does not require (de-)centralized simulation ...

In recent years, significant research efforts have been devoted to the optimal planning of power systems. Substation Expansion Planning (SEP) as a sub-system of power system planning consists of finding the most economical solution with the optimal location and size of future substations and/or feeders to meet the future demand. The large number of design variables, and combination of discrete ...