Models for Identifying Structures in the Data: A Performance Comparison

This paper reports on the unsupervised analysis of seismic signals recorded in Italy, respectively on the Vesuvius volcano, located in Naples, and on the Stromboli volcano, located North of Eastern Sicily. The Vesuvius dataset is composed of earthquakes and false events like thunders, man-made quarry and undersea explosions. The Stromboli dataset consists of explosion-quakes, landslides and volcanic microtremor signals. The aim of this paper is to apply on these datasets three projection methods, the linear Principal Component Analysis (PCA), the Self-Organizing Map (SOM), and the Curvilinear Component Analysis (CCA), in order to compare their performance. Since these algorithms are well known to be able to exploit structures and organize data providing a clear framework for understanding and interpreting their relationships, this work examines the category of structural information that they can provide on our specific sets. Moreover, the paper suggests a breakthrough in the applicati...

• Type: Conference
• Year: 2007
• Where: KES
• Authors: Anna Esposito, Antonietta M. Esposito, Flora Giudicepietro, Maria Marinaro, Silvia Scarpetta
• Keywords: KES 2007, Seismic Signals, Stromboli Volcano, Vesuvius Volcano