Now showing items 1-6 of 6
EXTRACTION OF UNDERLYING GEOLOGICAL STRUCTURE FROM SEISMIC DATA USING DATA MINING TECHNIQUES
The development of seismic-imaging technology has substantially improved the exploration of subsurface deposits of crude oil, natural gas and minerals. Recent advances in data capture, processing power and storage capabilities ...
Using Machine Learning for Automatic Classification of Classical Cepheids
With the increasing amounts of astronomical data being gathered, it is becoming more crucial for machine learning techniques to be employed for star classification. Classical Cepheid variable stars can be grouped into ...
Big Data Analysis of Complex Networks Using Machine Learning Methods
With the tremendous development of the modern complex networks such as smart grid and wireless communication domains, the data analysis tasks are significantly involved. In smart grid systems, there are emerging concerns ...
Cluster Validation of WHAN Galaxy Classification Using a Novel Approach To External Cluster Validation
The classification of galaxies is traditionally carried out using human-eye analysis of morphology or through information provided by a large survey of galaxies. Clustering methods can reduce the effort of manual classification ...
INFORMATION GAIN FEATURE SELECTION BASED ON FEATURE INTERACTIONS
Analyzing high-dimensional data stands as a great challenge in machine learning. In order to deal with the curse of dimensionality, many effective and efficient feature-selection algorithms have been developed recently. ...
Scalable Machine Learning Algorithms in Parallel Database Systems Exploiting A Data Summarization Matrix
Data summarization is an essential mechanism to accelerate analytic algorithms on large data sets. In this work we present a comprehensive data summarization matrix, namely the Gamma matrix, from which we can derive ...