Alejandra Rodriguez - Academia.edu (original) (raw)

Papers by Alejandra Rodriguez

Research paper thumbnail of A Comparative Study of KBS, ANN and Statistical Clustering Techniques for Unattended Stellar Classification

The purpose of this work is to present a comparative analysis of knowledge-based systems, artific... more The purpose of this work is to present a comparative analysis of knowledge-based systems, artificial neural networks and statistical clustering algorithms applied to the classification of low resolution stellar spectra. These techniques were used to classify a sample of approximately 258 optical spectra from public catalogues using the standard MK system. At present, we already dispose of a hybrid system that carries out this task, applying the most appropriate classification method to each spectrum with a success rate that is similar to that of human experts.

Research paper thumbnail of Hybrid Approach to MK Classification of Stars Neural Networks and Knowledge-based Systems

This paper presents a comparative study of the sensibility of knowledge-based systems and artific... more This paper presents a comparative study of the sensibility of knowledge-based systems and artificial neural networks applied to optical spectroscopy, a specific field of Astrophysics. We propose a description of various neural networks models and the comparison of the results obtained by each technique individually and by a combination of both. Whereas in previous works we developed a knowledge-based system for the automatic analysis of spectra, we shall now use the analysis methods developed in that system to extract the most important spectral features, by training the proposed neural networks with this numeric characterization. We do not only intend to analyse the efficiency of artificial neural networks in classification of stellar spectra; our approach is also focused on the integration of several artificial techniques in a unique hybrid system. The proposed system is capable of applying the most appropriate classification method to each spectrum, which widely opens the research in the field of automatic spectral classification.

Research paper thumbnail of Automated knowledge-based analysis and classification of stellar spectra using fuzzy reasoning

Expert Systems With Applications, 2004

This paper presents the application of artificial intelligence techniques to optical spectroscopy... more This paper presents the application of artificial intelligence techniques to optical spectroscopy, a specific field of Astrophysics. We propose the analysis, design and implementation of an intelligent system for the analysis and classification of the low-resolution optical spectra of supergiant, giant and dwarf stars, with luminosity levels I, III and V, respectively.

Research paper thumbnail of An Artificial Neural Network Approach to Automatic Classification of Stellar Spectra

This paper presents the design and implementation of several models of artificial neural networks... more This paper presents the design and implementation of several models of artificial neural networks for the automatic classification of low-resolution spectra of stars. In previous works, we have developed knowledge-based systems for the analysis of spectra. We shall now use these analysis methods to extract the most important spectral features, training the proposed neural networks with this numeric characterization. Although there are published works about neural networks applied to the classification problem, our final purpose is the integration of several artificial techniques in a unique hybrid system. In the development of such a system we have combined signal processing techniques, knowledge- based systems, fuzzy logic and artificial neural networks, integrating them by means of a relational database which allow us to structure the collected astronomical data and also contrast the results achieved with the different classification methods.

Research paper thumbnail of Hacia dónde va la ciencia política

Research paper thumbnail of A Comparative Study of KBS, ANN and Statistical Clustering Techniques for Unattended Stellar Classification

The purpose of this work is to present a comparative analysis of knowledge-based systems, artific... more The purpose of this work is to present a comparative analysis of knowledge-based systems, artificial neural networks and statistical clustering algorithms applied to the classification of low resolution stellar spectra. These techniques were used to classify a sample of approximately 258 optical spectra from public catalogues using the standard MK system. At present, we already dispose of a hybrid system that carries out this task, applying the most appropriate classification method to each spectrum with a success rate that is similar to that of human experts.

Research paper thumbnail of Hybrid Approach to MK Classification of Stars Neural Networks and Knowledge-based Systems

This paper presents a comparative study of the sensibility of knowledge-based systems and artific... more This paper presents a comparative study of the sensibility of knowledge-based systems and artificial neural networks applied to optical spectroscopy, a specific field of Astrophysics. We propose a description of various neural networks models and the comparison of the results obtained by each technique individually and by a combination of both. Whereas in previous works we developed a knowledge-based system for the automatic analysis of spectra, we shall now use the analysis methods developed in that system to extract the most important spectral features, by training the proposed neural networks with this numeric characterization. We do not only intend to analyse the efficiency of artificial neural networks in classification of stellar spectra; our approach is also focused on the integration of several artificial techniques in a unique hybrid system. The proposed system is capable of applying the most appropriate classification method to each spectrum, which widely opens the research in the field of automatic spectral classification.

Research paper thumbnail of Automated knowledge-based analysis and classification of stellar spectra using fuzzy reasoning

Expert Systems With Applications, 2004

This paper presents the application of artificial intelligence techniques to optical spectroscopy... more This paper presents the application of artificial intelligence techniques to optical spectroscopy, a specific field of Astrophysics. We propose the analysis, design and implementation of an intelligent system for the analysis and classification of the low-resolution optical spectra of supergiant, giant and dwarf stars, with luminosity levels I, III and V, respectively.

Research paper thumbnail of An Artificial Neural Network Approach to Automatic Classification of Stellar Spectra

This paper presents the design and implementation of several models of artificial neural networks... more This paper presents the design and implementation of several models of artificial neural networks for the automatic classification of low-resolution spectra of stars. In previous works, we have developed knowledge-based systems for the analysis of spectra. We shall now use these analysis methods to extract the most important spectral features, training the proposed neural networks with this numeric characterization. Although there are published works about neural networks applied to the classification problem, our final purpose is the integration of several artificial techniques in a unique hybrid system. In the development of such a system we have combined signal processing techniques, knowledge- based systems, fuzzy logic and artificial neural networks, integrating them by means of a relational database which allow us to structure the collected astronomical data and also contrast the results achieved with the different classification methods.

Research paper thumbnail of Hacia dónde va la ciencia política