Exploitation of Linkage Learning in Evolutionary Algorithms (Record no. 112147)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03602nam a22004935i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-642-12834-9 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20140220084536.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 100416s2010 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783642128349 |
| -- | 978-3-642-12834-9 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-3-642-12834-9 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | TA329-348 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | TA640-643 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | TBJ |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | MAT003000 |
| Source | bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 519 |
| Edition number | 23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Chen, Ying-ping. |
| Relator term | editor. |
| 245 10 - TITLE STATEMENT | |
| Title | Exploitation of Linkage Learning in Evolutionary Algorithms |
| Medium | [electronic resource] / |
| Statement of responsibility, etc | edited by Ying-ping Chen. |
| 264 #1 - | |
| -- | Berlin, Heidelberg : |
| -- | Springer Berlin Heidelberg, |
| -- | 2010. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 265p. 30 illus. in color. |
| Other physical details | online resource. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 490 1# - SERIES STATEMENT | |
| Series statement | Evolutionary Learning and Optimization, |
| International Standard Serial Number | 1867-4534 ; |
| Volume number/sequential designation | 3 |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Linkage and Problem Structures -- Linkage Structure and Genetic Evolutionary Algorithms -- Fragment as a Small Evidence of the Building Blocks Existence -- Structure Learning and Optimisation in a Markov Network Based Estimation of Distribution Algorithm -- DEUM – A Fully Multivariate EDA Based on Markov Networks -- Model Building and Exploiting -- Pairwise Interactions Induced Probabilistic Model Building -- ClusterMI: Building Probabilistic Models Using Hierarchical Clustering and Mutual Information -- Estimation of Distribution Algorithm Based on Copula Theory -- Analyzing the k Most Probable Solutions in EDAs Based on Bayesian Networks -- Applications -- Protein Structure Prediction Based on HP Model Using an Improved Hybrid EDA -- Sensible Initialization of a Computational Evolution System Using Expert Knowledge for Epistasis Analysis in Human Genetics -- Estimating Optimal Stopping Rules in the Multiple Best Choice Problem with Minimal Summarized Rank via the Cross-Entropy Method. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Engineering. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Mathematics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Engineering mathematics. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Engineering. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Appl.Mathematics/Computational Methods of Engineering. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial Intelligence (incl. Robotics). |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Applications of Mathematics. |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783642128332 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | Evolutionary Learning and Optimization, |
| -- | 1867-4534 ; |
| Volume number/sequential designation | 3 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-642-12834-9 |
| 912 ## - | |
| -- | ZDB-2-ENG |
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