Practical Handbook of Genetic Algorithms (Record no. 10570)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01532 a2200253 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250526161932.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250430041995xx 4 eng |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780849325298 |
| Qualifying information | BB |
| 037 ## - SOURCE OF ACQUISITION | |
| Source of stock number/acquisition | Taylor & Francis |
| Terms of availability | GBP 160.00 |
| Form of issue | BB |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | 01 |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | eng |
| 072 7# - SUBJECT CATEGORY CODE | |
| Subject category code | UY |
| Source | thema |
| 072 7# - SUBJECT CATEGORY CODE | |
| Subject category code | UB |
| Source | thema |
| 072 7# - SUBJECT CATEGORY CODE | |
| Subject category code | UY |
| Source | bic |
| 072 7# - SUBJECT CATEGORY CODE | |
| Subject category code | UB |
| Source | bic |
| 072 7# - SUBJECT CATEGORY CODE | |
| Subject category code | MAT000000 |
| Source | bisac |
| 072 7# - SUBJECT CATEGORY CODE | |
| Subject category code | MAT021000 |
| Source | bisac |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Lance D. Chambers |
| 9 (RLIN) | 904 |
| 245 10 - TITLE STATEMENT | |
| Title | Practical Handbook of Genetic Algorithms |
| Remainder of title | New Frontiers, Volume II |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1 |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Name of publisher, distributor, etc. | CRC Press |
| Date of publication, distribution, etc. | 19950815 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 448 p |
| 520 ## - SUMMARY, ETC. | |
| Expansion of summary note | The mathematics employed by genetic algorithms (GAs)are among the most exciting discoveries of the last few decades. But what exactly is a genetic algorithm? A genetic algorithm is a problem-solving method that uses genetics as its model of problem solving. It applies the rules of reproduction, gene crossover, and mutation to pseudo-organisms so those "organisms" can pass beneficial and survival-enhancing traits to new generations. GAs are useful in the selection of parameters to optimize a system's performance. A second potential use lies in testing and fitting quantitative models. Unlike any other book available, this interesting new text/reference takes you from the construction of a simple GA to advanced implementations. As you come to understand GAs and their processes, you will begin to understand the power of the genetic-based problem-solving paradigms that lie behind them. |
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