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- 2003049532 contributor B9539948.
- 2003049532 created "2003.".
- 2003049532 date "2003".
- 2003049532 date "2003.".
- 2003049532 dateCopyrighted "2003.".
- 2003049532 description "Includes bibliographical references and index.".
- 2003049532 extent "xviii, 383 p. :".
- 2003049532 identifier "0444513507 (hc. : alk. paper)".
- 2003049532 identifier 2003049532.html.
- 2003049532 identifier 2003049532.html.
- 2003049532 isPartOf "Data handling in science and technology, 0922-3487 ; v. 23".
- 2003049532 issued "2003".
- 2003049532 issued "2003.".
- 2003049532 language "eng".
- 2003049532 publisher "Amsterdam ; Boston : Elsevier,".
- 2003049532 subject "006.3/2 22".
- 2003049532 subject "Genetic algorithms.".
- 2003049532 subject "Neural networks (Computer science)".
- 2003049532 subject "QA76.87 .N3915 2003".
- 2003049532 title "Nature-inspired methods in chemometrics : genetic algorithms and artificial neural networks / edited by R. Leardi.".
- 2003049532 type "text".