Advances of Evolutionary Computation

Advances of Evolutionary Computation: Methods and Operators  eBooks & eLearning

Posted by Underaglassmoon at Jan. 24, 2016
Advances of Evolutionary Computation: Methods and Operators

Advances of Evolutionary Computation: Methods and Operators
Springer | Computational Intelligence and Complexity | January 7, 2016 | ISBN-10: 3319285025 | 202 pages | pdf | 15.78 mb

Authors: Cuevas, Erik, Díaz Cortés, Margarita Arimatea, Oliva Navarro, Diego Alberto
Discusses recent advances and alternative developments in Evolutionary Computation
Highlights nonconventional operators which prove to be effective in adapting a determined EC method to a specific problem
Consists of self-contained chapters that can be read independently from the others
Applications of Evolutionary Computation in Image Processing and Pattern Recognition (repost)

Erik Cuevas, Daniel Zaldívar, "Applications of Evolutionary Computation in Image Processing and Pattern Recognition"
2015 | ISBN: 3319264605 | 292 pages | PDF | 18 MB
Recent Advances in Evolutionary Computation for Combinatorial Optimization (repost)

Recent Advances in Evolutionary Computation for Combinatorial Optimization (Studies in Computational Intelligence) by Carlos Cotta and Jano Hemert
English | 1 edition | October 10, 2008 | ISBN-10: 3540708065 | 356 pages | PDF | 5.7 Mb

Evolutionary Computation for Dynamic Optimization Problems (repost)  eBooks & eLearning

Posted by interes at Dec. 5, 2014
Evolutionary Computation for Dynamic Optimization Problems (repost)

Evolutionary Computation for Dynamic Optimization Problems (Studies in Computational Intelligence) by Shengxiang Yang and Xin Yao
English | 2013-05-28 | ISBN: 3642384153 | 479 pages | PDF | 13,7 mb

Evolutionary Computation for Dynamic Optimization Problems (Repost)  eBooks & eLearning

Posted by Specialselection at Jan. 13, 2014
Evolutionary Computation for Dynamic Optimization Problems (Repost)

Shengxiang Yang, Xin Yao, "Evolutionary Computation for Dynamic Optimization Problems"
English | 2013-05-28 | ISBN: 3642384153 | 479 pages | PDF | 13.8 mb

Evolutionary Computation for Dynamic Optimization Problems  eBooks & eLearning

Posted by ChrisRedfield at Oct. 12, 2013
Evolutionary Computation for Dynamic Optimization Problems

Shengxiang Yang, ‎Xin Yao - Evolutionary Computation for Dynamic Optimization Problems
Published: 2013-05-28 | ISBN: 3642384153 | PDF | 500 pages | 13 MB
Recent Advances in Evolutionary Computation for Combinatorial Optimization (repost)

Recent Advances in Evolutionary Computation for Combinatorial Optimization (Studies in Computational Intelligence) by Carlos Cotta and Jano Hemert
English | 1 edition | October 10, 2008 | ISBN-10: 3540708065 | 356 pages | PDF | 5.7 Mb

Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. The intrinsic complexity of most combinatorial optimisation problems makes classical methods unaffordable in many cases.

Recent Advances in Evolutionary Computation for Combinatorial Optimization (repost)  eBooks & eLearning

Posted by rolexmaya at Nov. 22, 2011
Recent Advances in Evolutionary Computation for Combinatorial Optimization (repost)

Recent Advances in Evolutionary Computation for Combinatorial Optimization
Springer; 1 edition | October 10, 2008 | ISBN-10: 3540708065 | 356 pages | PDF | 5.7 Mb

Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. The intrinsic complexity of most combinatorial optimisation problems makes classical methods unaffordable in many cases.

Recent Advances in Evolutionary Computation for Combinatorial Optimization  eBooks & eLearning

Posted by karapuzik at Dec. 22, 2008
Recent Advances in Evolutionary Computation for Combinatorial Optimization

Recent Advances in Evolutionary Computation for Combinatorial Optimization (Studies in Computational Intelligence)
338 pages | Springer; 1 edition (October 10, 2008) | ISBN-10: 3540708065 | PDF | 5 Mb

Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. The intrinsic complexity of most combinatorial optimisation problems makes classical methods unaffordable in many cases. To acquire practical solutions to these problems requires the use of metaheuristic approaches that trade completeness for pragmatic effectiveness. Such approaches are able to provide optimal or quasi-optimal solutions to a plethora of difficult combinatorial optimisation problems.
Practical Applications of Evolutionary Computation to Financial Engineering[Repost]

Practical Applications of Evolutionary Computation to Financial Engineering: Robust Techniques for Forecasting, Trading and Hedging By Hitoshi Iba, Claus C. Aranha
2012 | 260 Pages | ISBN: 3642276474 | PDF | 7 MB