In this paper a Multi-objective Honey Bee Mating Optimization (MOHBMO) technique is applied to damp power system oscillation by tuning the Power System Stabilizer (PSS) parameters. Selecting the parameters of PSS which simultaneously stabilize system oscillations is converted to a simple optimization problem which is solved by a HBMO. In the proposed syndicate tuning technique, two performances...

Clustering is an important and popular technique in data mining. It partitions a set of objects in such a manner that objects in the same clusters are more similar to each another than objects in the different cluster according to certain predefined criteria. K-means is simple yet an efficient method used in data clustering. However, K-means has a tendency to converge to local optima and depend...

Multilevel thresholding is an important technique for image processing and pattern recognition. The maximum entropy thresholding (MET) has been widely applied in the literature. In this paper, a new multilevel MET algorithm based on the technology of the shuffled frog-leaping (SFLO) algorithm is proposed: called the maximum entropy based shuffled frog-leaping algorithm thresholding (MESFLOT) me...

Recently, Distribute Generation sources (DGs) connected to the distribution network has received increasing attention. The daily voltage control is one of the most important schemes in distribution networks, which can be affected by DGs. This paper presents a multi-objective Voltage optimizes control modeling, including objectives that are the total cost of power generated by Wind Farms (WFs) a...

Clustering techniques have received attention in many fields of study such as engineering, medicine, biology and data mining. The aim of clustering is to collect data points. The K-means algorithm is one of the most common techniques used for clustering. However, the results of K-means depend on the initial state and converge to local optima. In order to overcome local optima obstacles, a lot o...

Precise forecast of the electrical load plays a highly significant role in the electricity industry and market. It provides economic operations and effective future plans for the utilities and power system operators. Due to the intermittent and uncertain characteristic of the electrical load, many research studies have been directed to nonlinear prediction methods. In this paper, a hybrid predi...