Catálogo de publicaciones - libros
Evolutionary Computation in Dynamic and Uncertain Environments
Shengxiang Yang ; Yew-Soon Ong ; Yaochu Jin (eds.)
Resumen/Descripción – provisto por la editorial
No disponible.
Palabras clave – provistas por la editorial
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Disponibilidad
| Institución detectada | Año de publicación | Navegá | Descargá | Solicitá |
|---|---|---|---|---|
| No detectada | 2007 | SpringerLink |
Información
Tipo de recurso:
libros
ISBN impreso
978-3-540-49772-1
ISBN electrónico
978-3-540-49774-5
Editor responsable
Springer Nature
País de edición
Reino Unido
Fecha de publicación
2007
Información sobre derechos de publicación
© Springer Berlin Heidelberg 2007
Tabla de contenidos
Evolutionary Shape Optimization Using Gaussian Processes
Wenbin Song
The protection of privacy is an increasing concern in today’s global infrastructure. One of the most important privacy protection principles states that personal information collected for one purpose may not be used for any other purpose without the specific of the person it concerns. Although users provide personal information for use in one specific context, they often have no idea on how such a personal information may be used subsequently.
In this paper, we introduce a new type of privacy policy, called , which defines how the personal information release will be (or should be) dealt with at the receiving party. A data handling policy allows users to define simple and appropriate levels of control over who sees what information about them and under which circumstances.
Part II - Approximation of Fitness Functions | Pp. 251-267
A Study of Techniques to Improve the Efficiency of a Multi-Objective Particle Swarm Optimizer
Margarita Reyes-Sierra; Carlos A. Coello Coello
The protection of privacy is an increasing concern in today’s global infrastructure. One of the most important privacy protection principles states that personal information collected for one purpose may not be used for any other purpose without the specific of the person it concerns. Although users provide personal information for use in one specific context, they often have no idea on how such a personal information may be used subsequently.
In this paper, we introduce a new type of privacy policy, called , which defines how the personal information release will be (or should be) dealt with at the receiving party. A data handling policy allows users to define simple and appropriate levels of control over who sees what information about them and under which circumstances.
Part II - Approximation of Fitness Functions | Pp. 269-296
An Evolutionary Multi-objective Adaptive Meta-modeling Procedure Using Artificial Neural Networks
Kalyanmoy Deb; Pawan K. S. Nain
The protection of privacy is an increasing concern in today’s global infrastructure. One of the most important privacy protection principles states that personal information collected for one purpose may not be used for any other purpose without the specific of the person it concerns. Although users provide personal information for use in one specific context, they often have no idea on how such a personal information may be used subsequently.
In this paper, we introduce a new type of privacy policy, called , which defines how the personal information release will be (or should be) dealt with at the receiving party. A data handling policy allows users to define simple and appropriate levels of control over who sees what information about them and under which circumstances.
Part II - Approximation of Fitness Functions | Pp. 297-322
Surrogate Model-Based Optimization Framework: A Case Study in Aerospace Design
Yolanda Mack; Tushar Goel; Wei Shyy; Raphael Haftka
The protection of privacy is an increasing concern in today’s global infrastructure. One of the most important privacy protection principles states that personal information collected for one purpose may not be used for any other purpose without the specific of the person it concerns. Although users provide personal information for use in one specific context, they often have no idea on how such a personal information may be used subsequently.
In this paper, we introduce a new type of privacy policy, called , which defines how the personal information release will be (or should be) dealt with at the receiving party. A data handling policy allows users to define simple and appropriate levels of control over who sees what information about them and under which circumstances.
Part II - Approximation of Fitness Functions | Pp. 323-342
Hierarchical Evolutionary Algorithms and Noise Compensation via Adaptation
Ferrante Neri; Raino A. E. Mäkinen
The protection of privacy is an increasing concern in today’s global infrastructure. One of the most important privacy protection principles states that personal information collected for one purpose may not be used for any other purpose without the specific of the person it concerns. Although users provide personal information for use in one specific context, they often have no idea on how such a personal information may be used subsequently.
In this paper, we introduce a new type of privacy policy, called , which defines how the personal information release will be (or should be) dealt with at the receiving party. A data handling policy allows users to define simple and appropriate levels of control over who sees what information about them and under which circumstances.
Part III - Handling Noisy Fitness Functions | Pp. 345-369
Evolving Multi Rover Systems in Dynamic and Noisy Environments
Kagan Tumer; Adrian Agogino
The protection of privacy is an increasing concern in today’s global infrastructure. One of the most important privacy protection principles states that personal information collected for one purpose may not be used for any other purpose without the specific of the person it concerns. Although users provide personal information for use in one specific context, they often have no idea on how such a personal information may be used subsequently.
In this paper, we introduce a new type of privacy policy, called , which defines how the personal information release will be (or should be) dealt with at the receiving party. A data handling policy allows users to define simple and appropriate levels of control over who sees what information about them and under which circumstances.
Part III - Handling Noisy Fitness Functions | Pp. 371-387
A Memetic Algorithm Using a Trust-Region Derivative-Free Optimization with Quadratic Modelling for Optimization of Expensive and Noisy Black-box Functions
Yoel Tenne; Steven William Armfield
The protection of privacy is an increasing concern in today’s global infrastructure. One of the most important privacy protection principles states that personal information collected for one purpose may not be used for any other purpose without the specific of the person it concerns. Although users provide personal information for use in one specific context, they often have no idea on how such a personal information may be used subsequently.
In this paper, we introduce a new type of privacy policy, called , which defines how the personal information release will be (or should be) dealt with at the receiving party. A data handling policy allows users to define simple and appropriate levels of control over who sees what information about them and under which circumstances.
Part III - Handling Noisy Fitness Functions | Pp. 389-415
Genetic Algorithm to Optimize Fitness Function with Sampling Error and its Application to Financial Optimization Problem
Masaru Tezuka; Masaharu Munetomo; Kiyoshi Akama
The protection of privacy is an increasing concern in today’s global infrastructure. One of the most important privacy protection principles states that personal information collected for one purpose may not be used for any other purpose without the specific of the person it concerns. Although users provide personal information for use in one specific context, they often have no idea on how such a personal information may be used subsequently.
In this paper, we introduce a new type of privacy policy, called , which defines how the personal information release will be (or should be) dealt with at the receiving party. A data handling policy allows users to define simple and appropriate levels of control over who sees what information about them and under which circumstances.
Part III - Handling Noisy Fitness Functions | Pp. 417-434
Single/Multi-objective Inverse Robust Evolutionary Design Methodology in the Presence of Uncertainty
Dudy Lim; Yew-Soon Ong; Meng-Hiot Lim; Yaochu Jin
The protection of privacy is an increasing concern in today’s global infrastructure. One of the most important privacy protection principles states that personal information collected for one purpose may not be used for any other purpose without the specific of the person it concerns. Although users provide personal information for use in one specific context, they often have no idea on how such a personal information may be used subsequently.
In this paper, we introduce a new type of privacy policy, called , which defines how the personal information release will be (or should be) dealt with at the receiving party. A data handling policy allows users to define simple and appropriate levels of control over who sees what information about them and under which circumstances.
Part IV - Search for Robust Solutions | Pp. 437-456
Evolving the Tradeoffs between Pareto-Optimality and Robustness in Multi-Objective Evolutionary Algorithms
Chi Keong Goh; Kay Chen Tan
The protection of privacy is an increasing concern in today’s global infrastructure. One of the most important privacy protection principles states that personal information collected for one purpose may not be used for any other purpose without the specific of the person it concerns. Although users provide personal information for use in one specific context, they often have no idea on how such a personal information may be used subsequently.
In this paper, we introduce a new type of privacy policy, called , which defines how the personal information release will be (or should be) dealt with at the receiving party. A data handling policy allows users to define simple and appropriate levels of control over who sees what information about them and under which circumstances.
Part IV - Search for Robust Solutions | Pp. 457-478