An introduction to genetic algorithms / Melanie Mitchell.
نوع المادة : نصالسلاسل:Complex adaptive systemsالناشر:Cambridge, Mass. : MIT Press, [1998]تاريخ حقوق النشر: ©1996الطبعات:1st MIT Press pbk. edوصف:viii, 209 pages : illustrations ; 26 cmنوع المحتوى:- text
- unmediated
- volume
- 0262631857
- 9780262631853
- 0262133164
- 9780262133166
- QA402.5 .M58 1998
- Also available via the World Wide Web.
نوع المادة | المكتبة الحالية | رقم الطلب | رقم النسخة | حالة | تاريخ الإستحقاق | الباركود | |
---|---|---|---|---|---|---|---|
كتاب | UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة | QA402.5 .M58 1998 (إستعراض الرف(يفتح أدناه)) | C.1 | Library Use Only | داخل المكتبة فقط | 30010011104562 | ||
كتاب | UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة | QA402.5 .M58 1998 (إستعراض الرف(يفتح أدناه)) | C.2 | المتاح | 30010011104528 |
Browsing UAE Federation Library | مكتبة اتحاد الإمارات shelves, Shelving location: General Collection | المجموعات العامة إغلاق مستعرض الرف(يخفي مستعرض الرف)
QA402.5 .M4148 2012 Metaheuristics in water, geotechnical and transport engineering / | QA402.5 .M4148 2012 Metaheuristics in water, geotechnical and transport engineering / | QA402.5 .M58 1998 An introduction to genetic algorithms / | QA402.5 .M58 1998 An introduction to genetic algorithms / | QA402.5 .M858 2008 Multiobjective optimization : interactive and evolutionary approaches / | QA402.5 .M858 2008 Multiobjective optimization : interactive and evolutionary approaches / | QA402.5 .S6378 2017 Smart city networks : through the Internet of Things / |
"A Bradford book."
Includes appendices.
Includes bibliographical references (pages 191-201) and index.
1. Genetic Algorithms: An Overview --- 2. Genetic Algorithms in Problem Solving --- 3. Genetic Algorithms in Scientific Models --- 4. Theoretical Foundations of Genetic Algorithms --- 5. Implementing a Genetic Algorithm --- 6. Conclusions and Future Directions.
Also available via the World Wide Web.
"Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics - particularly in machine learning, scientific modeling, and artificial life - and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics."--Publisher description.