The Cooperative Target Observation (CTO) problem has been of great interest in the multi-agents and robotics literature due to the problem being at the core of a number of applications including surveillance. In CTO problem, the observer agents attempt to maximize the collective time during which each moving target is being observed by at least one observer in the area of interest. However, mos...

In this paper, we evaluate the player segmentation for trajectory estimation in soccer games. In order to estimate the field trajectories of players in soccer games, we should accurately locate the foot positions of players in each soccer image and transform them into those in the soccer field. However, we cannot always segment the players completely, since players are often motion-blurred due ...

Cluster analysis is a fundamental technique for various filed such as pattern recognition, machine learning and so forth. However, the cluster number is predefined by users in K-means algorithm, which is unpractical to implement. Since the number of clusters is a NP-complete problem, Genetic Algorithm is employed to solve it. In addition, due to the large time consuming in conventional method, ...

Through comparison and analysis of clustering algorithms, this paper presents an improved Kmeans clustering algorithm. Using genetic algorithm to select the initial cluster centers, using Z-score to standardize data, and take a new method to evaluate cluster centers, all this reduce the affect of isolated points, and improve the accuracy of clustering. Experiments show that the algorithm to fin...

In this paper, the well-known k-means algorithm for searching for a locally 12 optimal partition of the setA ⊂ R is analyzed in the case if some data points occur on the 13 border of two or more clusters. For this special case, a useful strategy by implementation 14 of the k-means algorithm is proposed. 15

The clustering is a without monitoring process and one of the most common data mining techniques. The purpose of clustering is grouping similar data together in a group, so were most similar to each other in a cluster and the difference with most other instances in the cluster are. In this paper we focus on clustering partition k-means, due to ease of implementation and high-speed performance o...

Finding the collapse susceptible portion of a power system is one of the purposes of voltage stability analysis. This part which is a voltage control area is called the voltage weak area. Determining the weak area and adjecent voltage control areas has special importance in the improvement of voltage stability. Designing an on-line corrective control requires the voltage weak area to be determi...

Finding the collapse susceptible portion of a power system is one of the purposes of voltage stability analysis. This part which is a voltage control area is called the voltage weak area. Determining the weak area and adjecent voltage control areas has special importance in the improvement of voltage stability. Designing an on-line corrective control requires the voltage weak area to be determi...

We consider the popular k-means problem in d-dimensional Euclidean space. Recently Friggstad, Rezapour, Salavatipour [FOCS’16] and Cohen-Addad, Klein, Mathieu [FOCS’16] showed that the standard local search algorithm yields a p1`εq-approximation in time pn ̈kq Opdq , giving the first polynomialtime approximation scheme for the problem in low-dimensional Euclidean space. While local search achiev...