ying ping chen (28 Ergebnisse)

Hardcover. First Edition. Octavo, viii, 246 pages. In Very Good minus condition. Bound in red and purple paper with white and yellow lettering. Boards have minor shelf wear. Text block has minor cracking to gutter of title page. NOTE: Shelved in ND-E. 1377100. FP New Rockville Stock.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New. In.

Zustand: New. In.

Zustand: New. In.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 256 | Sprache: Englisch | Produktart: Bücher | One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of linkage. In evolutionary algorithms, linkage models the relation between decision variables with the genetic linkage observed in biological systems, and linkage learning connects computational optimization methodologies and natural evolution mechanisms. Exploitation of linkage learning can enable us to design better evolutionary algorithms as well as to potentially gain insight into biological systems. Linkage learning has the potential to become one of the dominant aspects of evolutionary algorithms; research in this area can potentially yield promising results in addressing the scalability issues.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 500 | Sprache: Englisch | Produktart: Bücher | In recent years, the issue of linkage in GEAs has garnered greater attention and recognition from researchers. Conventional approaches that rely much on ad hoc tweaking of parameters to control the search by balancing the level of exploitation and exploration are grossly inadequate. As shown in the work reported here, such parameters tweaking based approaches have their limits; they can be easily ¿fooled¿ by cases of triviality or peculiarity of the class of problems that the algorithms are designed to handle. Furthermore, these approaches are usually blind to the interactions between the decision variables, thereby disrupting the partial solutions that are being built up along the way.

Zustand: New. pp. 258 Illus.

Paperback. Zustand: Brand New. 140 pages. 9.25x6.00x0.32 inches. In Stock.

Paperback. Zustand: Brand New. 2010 edition. 256 pages. 9.20x6.10x0.61 inches. In Stock.

Hardcover. Zustand: Brand New. 265 pages. 9.50x6.50x0.75 inches. In Stock.

Taschenbuch. Zustand: Neu. Extending the Scalability of Linkage Learning Genetic Algorithms | Theory & Practice | Ying-Ping Chen | Taschenbuch | Studies in Fuzziness and Soft Computing | xx | Englisch | 2010 | Springer | EAN 9783642066719 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Exploitation of Linkage Learning in Evolutionary Algorithms | Ying-Ping Chen | Taschenbuch | Adaptation, Learning, and Optimization | x | Englisch | 2012 | Springer | EAN 9783642263279 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Zustand: New. In.

Zustand: New. Advances our understanding of the linkage learning genetic algorithm and demonstrates potential research directionsGenetic algorithms (GAs) are powerful search techniques based on principles of evolution and widely applied to solve problems in.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Genetic algorithms (GAs) are powerful search techniques based on principles of evolution and widely applied to solve problems in many disciplines. However, most GAs employed in practice nowadays are unable to learn genetic linkage and suffer from the linkage problem. The linkage learning genetic algorithm (LLGA) was proposed to tackle the linkage problem with several specially designed mechanisms. While the LLGA performs much better on badly scaled problems than simple GAs, it does not work well on uniformly scaled problems as other competent GAs. Therefore, we need to understand why it is so and need to know how to design a better LLGA or whether there are certain limits of such a linkage learning process. This book aims to gain better understanding of the LLGA in theory and to improve the LLGA's performance in practice. It starts with a survey of the existing genetic linkage learning techniques and describes the steps and approaches taken to tackle the research topics, including using promoters, developing the convergence time model, and adopting subchromosomes.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of linkage. In evolutionary algorithms, linkage models the relation between decision variables with the genetic linkage observed in biological systems, and linkage learning connects computational optimization methodologies and natural evolution mechanisms. Exploitation of linkage learning can enable us to design better evolutionary algorithms as well as to potentially gain insight into biological systems. Linkage learning has the potential to become one of the dominant aspects of evolutionary algorithms; research in this area can potentially yield promising results in addressing the scalability issues.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of linkage. In evolutionary algorithms, linkage models the relation between decision variables with the genetic linkage observed in biological systems, and linkage learning connects computational optimization methodologies and natural evolution mechanisms. Exploitation of linkage learning can enable us to design better evolutionary algorithms as well as to potentially gain insight into biological systems. Linkage learning has the potential to become one of the dominant aspects of evolutionary algorithms; research in this area can potentially yield promising results in addressing the scalability issues.

Taschenbuch. Zustand: Neu. Linkage in Evolutionary Computation | Ying-Ping Chen | Taschenbuch | Studies in Computational Intelligence | xii | Englisch | 2010 | Springer | EAN 9783642098765 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Zustand: New. In.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In recent years, the issue of linkage in GEAs has garnered greater attention and recognition from researchers. Conventional approaches that rely much on ad hoc tweaking of parameters to control the search by balancing the level of exploitation and exploration are grossly inadequate. As shown in the work reported here, such parameters tweaking based approaches have their limits; they can be easily 'fooled' by cases of triviality or peculiarity of the class of problems that the algorithms are designed to handle. Furthermore, these approaches are usually blind to the interactions between the decision variables, thereby disrupting the partial solutions that are being built up along the way.

Zustand: New. In.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In recent years, the issue of linkage in GEAs has garnered greater attention and recognition from researchers. Conventional approaches that rely much on ad hoc tweaking of parameters to control the search by balancing the level of exploitation and exploration are grossly inadequate. As shown in the work reported here, such parameters tweaking based approaches have their limits; they can be easily 'fooled' by cases of triviality or peculiarity of the class of problems that the algorithms are designed to handle. Furthermore, these approaches are usually blind to the interactions between the decision variables, thereby disrupting the partial solutions that are being built up along the way.

Hardcover. Zustand: Brand New. 1st edition. 488 pages. 9.25x6.25x1.25 inches. In Stock.

Hardcover. Zustand: Near Fine. Zustand des Schutzumschlags: dj. In a slipcase. Text in Chinese. 336 pp. Dust jacket has slight rubbing. Worn Slipcase.

Softcover. Zustand: g to vg. First edition. Oblong quarto (9 1/2 x 10 1/4"). [4]pp (Title and Introduction); [48]pp (Plates); [2]pp. Original photo-illustrated dust-jacket over blind wrappers. Illustrated with 48 striking photogravures (13 in full color) depicting some of the most spectacular and dizzying views of China, this scarce Spanish-language photo-book* takes us on a journey filled with the richness and diversity of its landscapes and culture. Dust-jacket partly rubbed along edges, with close tear and minor chipping at head of spine. Text in Spanish. Dust-jacket in overall good, wrappers and interior in very good condition. * The book is not in Parr, and OCLC indicates only three libraries worlwide owning it.