Simulated Evolution and Learning [electronic resource] : 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, 2014. Proceedings / edited by Grant Dick, Will N. Browne, Peter Whigham, Mengjie Zhang, Lam Thu Bui, Hisao Ishibuchi, Yaochu Jin, Xiaodong Li, Yuhui Shi, Pramod Singh, Kay Chen Tan, Ke Tang.

By:

Dick, Grant [editor.]

Contributor(s):

Material type: Text

TextSeries: Lecture Notes in Computer Science ; 8886Publisher: Cham : Springer International Publishing : Imprint: Springer, 2014Description: XVI, 862 p. 267 illus. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783319135632

Subject(s):

Additional physical formats: Printed edition:: No titleDDC classification:

004.0151 23

LOC classification:

QA75.5-76.95

Online resources:

Click here to access online

Contents:

Evolutionary optimization -- Evolutionary multi-objective optimization -- Evolutionary machine learning -- Theoretical developments -- Evolutionary feature reduction -- Evolutionary scheduling and combinatorial optimization -- Real world applications and evolutionary image analysis.

In: Springer eBooksSummary: This volume constitutes the proceedings of the 10th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Dunedin, New Zealand, in December 2014. The 42 full papers and 29 short papers presented were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on evolutionary optimization; evolutionary multi-objective optimization; evolutionary machine learning; theoretical developments; evolutionary feature reduction; evolutionary scheduling and combinatorial optimization; real world applications and evolutionary image analysis.

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Holdings
Item type	Current library	Call number	Status	Date due	Barcode
E-Book	Central Library		Available		E-42294

This volume constitutes the proceedings of the 10th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Dunedin, New Zealand, in December 2014. The 42 full papers and 29 short papers presented were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on evolutionary optimization; evolutionary multi-objective optimization; evolutionary machine learning; theoretical developments; evolutionary feature reduction; evolutionary scheduling and combinatorial optimization; real world applications and evolutionary image analysis.

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