Hybrid Genetic-Fuzzy Algorithm for Variable Selection in Spectroscopy
This paper presents a hybrid multi-objective genetic fuzzy algorithm for the variable-selection problem in spectroscopy. The problem formulation considers three fitness functions related to linear equations system stability. These fitness functions are models with fuzzy sets that evaluate the fitnes...
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| Published in | Artificial Intelligence and Soft Computing pp. 24 - 35 |
|---|---|
| Main Authors | , , , , |
| Format | Book Chapter |
| Language | English |
| Published |
Berlin, Heidelberg
Springer Berlin Heidelberg
2013
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| Series | Lecture Notes in Computer Science |
| Subjects | |
| Online Access | Get full text |
| ISBN | 3642386091 9783642386091 |
| ISSN | 0302-9743 1611-3349 |
| DOI | 10.1007/978-3-642-38610-7_3 |
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| Abstract | This paper presents a hybrid multi-objective genetic fuzzy algorithm for the variable-selection problem in spectroscopy. The problem formulation considers three fitness functions related to linear equations system stability. These fitness functions are models with fuzzy sets that evaluate the fitness solution for pick out the best to crossover. The population diversity is obtained applying the crowding distance method. The study shows that the selection by a fuzzy decision has better results than the selection by non-domination in problems where the fitness weighing is more proper than no-domination solutions. |
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| AbstractList | This paper presents a hybrid multi-objective genetic fuzzy algorithm for the variable-selection problem in spectroscopy. The problem formulation considers three fitness functions related to linear equations system stability. These fitness functions are models with fuzzy sets that evaluate the fitness solution for pick out the best to crossover. The population diversity is obtained applying the crowding distance method. The study shows that the selection by a fuzzy decision has better results than the selection by non-domination in problems where the fitness weighing is more proper than no-domination solutions. |
| Author | Coelho, Clarimar José Laureano, Gustavo Teodoro da Silva Soares, Anderson Salvini, Rogério Lopes de Lima, Telma Woerle |
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| Copyright | Springer-Verlag Berlin Heidelberg 2013 |
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| DOI | 10.1007/978-3-642-38610-7_3 |
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| Discipline | Engineering Computer Science |
| EISBN | 3642386105 9783642386107 |
| EISSN | 1611-3349 |
| Editor | Scherer, Rafał Zadeh, Lotfi A. Tadeusiewicz, Ryszard Zurada, Jacek M. Rutkowski, Leszek Korytkowski, Marcin |
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| Snippet | This paper presents a hybrid multi-objective genetic fuzzy algorithm for the variable-selection problem in spectroscopy. The problem formulation considers... |
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| SubjectTerms | Fuzzy logic Multi-objective Genetic Algorithm Variable Selection |
| Title | Hybrid Genetic-Fuzzy Algorithm for Variable Selection in Spectroscopy |
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