Artificial immune systems and their applications

著者

書誌事項

Artificial immune systems and their applications

Dipankar Dasgupta (ed.)

Springer, c1999

大学図書館所蔵 件 / 全25件

この図書・雑誌をさがす

注記

Includes bibliographical references and index

内容説明・目次

内容説明

Artificial immune systems are highly distributed systems based on the principles of the natural system. This is a new and rapidly growing field offering powerful and robust information processing capabilities for solving complex problems. Like artificial neural networks, artificial immune systems can learn new information, recall previously learned information, and perform pattern recognition in a highly decentralized fashion. This volume provides an overview of the immune system from the computational viewpoint. It discusses computational models of the immune system and their applications, and provides a wealth of insights on immunological memory and the effects of viruses in immune response. It will be of professional interest to scientists, academics, vaccine designers, and practitioners.

目次

  • Introduction - An Overview of Artificial Immune Systems
  • The Central and the Peripheral Immune Systems: What is the Relationship?- Immune Network: An Example of Complex Adaptive Systems
  • Immunology Viewed as the Study of an Autonomous Decentralized System
  • The Endogenous Double Plasticity of the Immune Network and the Inspiration to be Drawn for Engineering Artifacts
  • Immunological Memory is Associative
  • Jisys: The Development of an Artificial Immune System for Real World Applications
  • Decentralized Behavior Arbitration Mechanism for Autonomous Mobile Robot Using Immune Network
  • Parallel Search for Multi-Modal Function Optimization with Diversity and Learning of Immune Algorithm
  • Immunized Adaptive Critic for an Autonomous Aircraft Control Application
  • Blueprint for a Computer Immune System
  • An Anomaly Detection Algorithm Inspired by the Immune System
  • Immunity Based Management System for a Semiconductor Production Line
  • Estimating and Predicting the Numbers of Free HIV and Different Types of T Cells in HIV-Infected Individuals by Nonlinear Kalman Filter
  • Modeling the Effects of Prior Infection on Vaccine Efficacy.

「Nielsen BookData」 より

詳細情報

ページトップへ