Coordinating technology: Studies in the international standarization of telecommunications: By S. K. Schmidt and Raymund Werle. MIT Press, Cambridge, MA. (1998). 365 pages. $35.00
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 111 KB
- Volume
- 35
- Category
- Article
- ISSN
- 0898-1221
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✦ Synopsis
Contents: Preface. Acknowledgements. List of Contributors. 1. Artificial evolution: How and why? (H-P. Schwefel and T. B~ck). Adaptive niching via coevolutionary sharing (D. Goldberg and L. Wang). 3. Representation issues in neighbourhood search and evolutionary algorithms (D. Whitley, S. Rana and R. Heckendorn). 4. Gene expression: The missing link in evolutionary computation (H. Kargupta). 5. Immunized artificial systems--Concepts and applications (K. Krishnakumar and J. Neidhoefer). 6. Designing electronic circuits using evolutionary algorithms arithmetic circuits: A case study (J.F. Miller, P. Thomson and T. Fogarty). 7. Evolutionary computing for conceptual and detailed design (I.C. Parmee). 8. Cam shape optimization by genetic algorithms (J.T. Alander and J. Lampinen). 9. Evolutionary algorithms: Applications at the Informatik Center Dortmund (T. Biick et al.). 10. Evolutionary learning processes for data analysis in electrical engineering applications (O. Corddn, F. Herrera and L. S~nche~). 11. Ga multiple objective optimization strategies for electromagnetic backscattering (J. Pdriaux, M. Sefrioui and B. Mantel). 12. Pareto genetic algorithm for aerodynamic design using the Navier-Stokes equations (S. Obayashi). GA coupled with computationally expensive simulations: Tools to improve efficiency (G. Poloni and V. Pediroda). 14. Coupling genetic algorithms and gradient based optimization techniques (D. Quagliarella and A. Vicini). 15. Evolutionary synthesis of control policies for manufacturing systems (B. Porter). 16. Parametric and non-parametric identification of macro-mechanical models (M. Sebag, M. Schoenauer and H. Maitournam). 17. Evolutionary mobile robotics (D. Floreano). 18. Nonlinear system identification by means of evolutionary optimised neural networks (I. De Falco).