Particle swarm optimization (PSO) has been employed on several optimization problems, including the clustering problem. PSO has also been employed in the clustering of data of different structure and dimensionality. In this paper it is employed in the clustering of nucleic acid sequences. The application of clustering, as a statistical tool, in the analysis of data of varied complexity has been...

Clustering merupakan proses pengelompokan sekumpulan data ke dalam klaster yang memiliki kemiripan. Kemiripan satau ditentukan dengan perhitungan jarak. Untuk melihat perfoma beberapa jarak, penelitian ini penulis menguji pada 6 atribut berbeda, yakni 2, 3, 4, dan atribut. Dari hasil uji perbandingan rumus jarak K-Means clustering menggunakan Silhouette coefficient dapat disimpulkan bahwa: 1) C...

This study will observe the process of grouping data or forming clusters using K-Means with three methods measuring distances, namely Euclidean distance, Manhattan and Minkowski distance. Observations are more focused on changing centroid value results data, as well number iterations required. Experimental amounted to 20, 30, 40, 50 pieces which were grouped into 2 groups. research also summari...

Drought resistance breeding provides a hopeful way to improve yield and quality of wheat in arid and semiarid regions. Constructing core collection is an efficient way to evaluate and utilize drought-resistant germplasm resources in wheat. In the present research, 1,683 wheat varieties were divided into five germplasm groups (high resistant, HR; resistant, R; moderate resistant, MR; susceptible...

The work presented in this paper focuses on recognition of isolated handwritten characters in Devanagari and Gurumukhi script. The proposed work uses four feature extraction methods like Zoning density, Projection histograms, Distance profiles and Background Directional Distribution(BDD). On the basis of these four types of features we have formed 10 feature vectors using different combinations...

We have applied the concept of fractional distance measures, proposed by Aggarwal et al. [1], to content-based image retrieval. Our experiments show that retrieval performances of these measures consistently outperform the more usual Manhattan and Euclidean distance metrics when used with a wide range of high-dimensional visual features. We used the parameters learnt from a Corel dataset on a v...

Now day’s Outlier Detection is used in various fields such as Credit Card Fraud Detection, Cyber-Intrusion Detection, Medical Anomaly Detection, and Data Mining etc. So to detect anomaly objects from various types of dataset Outlier Detection techniques are used, that detects and remove the anomaly objects from the dataset. Outliers are the containments that divert from the other objects. Outli...

A staircase in this paper is the set of points in Z2 below a given rational line in the plane that have Manhattan Distance less than 1 to the line. Staircases are closely related to Beatty and Sturmian sequences of rational numbers. Connecting the geometry and the number theoretic concepts, we obtain three equivalent characterizations of Sturmian sequences of rational numbers, as well as a new ...