计算智能及其应用

计算智能及其应用

姚新, 李学龙, 陶大程, 著

出版社:中国科学技术大学出版社

年代:2009

定价:68.0

书籍简介:

本书从信息预测与处理、生物计算、系统仿真等诸多领域阐述了计算智能的关键应用。全书共分作11章,依次介绍了智能计算在自适应粒子过滤器、基于内容的图像检索、记录分析及预测模型、自适应数据库系统入侵、人工神经网络应用软件的可靠性、蛋白质三级结构预测、递归的非参数判别分析的目标检测、基于隐私保护特性的预测的摄动技术、贝叶斯网络建模软件检查、智能仿真一体化、智能视频内容分析等方面的应用情况。本书可供相关领域的研究生和科研技术人员参考。

书籍目录:

Preface to the USTC Alumnis Series

Preface

1 Adaptive Particle Filters

1.1 Bayesian Filtering for Dynamic State Estimation

1.1.1 State and Observation Models

1.1.2 Bayesian Filtering Method

1.2 Fundamentals of Particle Filters

1.2.1 Sequential Monte Carlo Method

1.2.2 Basic Particle Filtering Algorithms

1.3 Challenging Issues in Particle Filtering

1.3.1 Unknown or Varying State Model

1.3.2 Construction of Proposal Density

1.3.3 Determination of Sample Size

1.3.4 Curse of Dimensionality

1.4 Adaptive Particle Filtering Algorithms

1.4.1 Algorithms with Adaptive Sample Size.

1.4.2 Algorithms with Adaptive Proposal:Density

1.4.3 Other Related Algorithms

1.5 Summary

References

Brief Introduction of Authors

2 Feature Localization and Shape Indexing for ContentBased Image Retrieval

2.1 Introduction

2.2 Locales for Feature Localization

2.3 Search by Object Model

2.4 Shape Indexing and Recognition

2.5 Experimental Results

2.5.1 Search Using Locale-based Models

2.5.2 Video Locales

2.5.3 Shape Indexing and Recognition

2.6 Conclusion

References

Brief Introduction of Authors

3 BlueGene/L Failure Analysis and Prediction Models

3.1 Introduction

3.2 BlueGene/L Architecture, RAS Event Logs, and Job Logs

3.2.1 BlueGene/L Architecture

3.2.2 RAS Event Logs

3.2.3 Job Logs

3.3 Impact of Failures on Job Executions

3.4 Failure Prediction Based on Failure Characteristics

3.4.1 Temporal Characteristics

3.4.2 Spatial Characteristics

3.5 Predicting Failures Using the Occurrence of Non-Fatal Events

3.6 Related Work

3.7 Concluding Remarks and Future Directions

References

Brief Introduction of Authors

4 A Neuro-Fuzzy Approach towards Adaptive IntrusionTolerant Database Systems

4.1 Overview

4.2 ITDB architecture

4.3 The Need for Adaptivity

4.4 Intelligent Techniques Solutions in AdaptiveITDB

4.5 Intelligent Techniques Solutions in AdaptiveITDB

4.6 The Design of Reconfiguration Components

4.7 Performance Metrics for Adaptive ITDB

4.8 Adaptation Criteria

4.9 The Rule-Based Adaptive Controller

4.10 The Neuro-Fuzzy Adaptive Controller

4.11 The collection of training data

4.12 Evaluation Methodology

4.12.1 Transaction Simulation

4.12.2 Evaluation Criteria

4.13 Evaluation of NFAC and RBAC Performance

4.14 Conclusion

4.15 Future Work

References

Brief Introduction of Authors

5 Artificial Neural Network Applications in Software Re-liability

5.1 Introduction

5.2 Analytical Software Reliability Models

5.3 ANN Models

5.3.1 Model I-Traditional ANN Modeling

5.3.2 Model II- FDP&FCP Modeling

5.3.3 Models III- Early Prediction Modeling

5.4 Numerical Applications

5.4.1 Applications of Traditional ANN Models

5.4.2 Applications of FDP&FCP ANN Models

5.4.3 Applications of Early Prediction ANN Models

5.5 Conclusions and Discussions

References

Brief Introduction of Authors

6 A New Computational Intelligent Approach to Protein Tertiary Structure Prediction

6.1 Introduction

6.2 New Fragment Retrieval Methods

6.2.1 Fragment Retrieval Using BLAST

6.2.2 Information Content of Retrieved Fragments

6.2.3 Whole Template Retrieval Using Secondary Structures

6.3 New Protein 3-D Structure Prediction Methods

6.3.1 Multidimensional Scaling (MDS) Methods

6.3.2 MDS-based Structure Prediction

6.3.3 Refinement Using Local Optimization

6.3.4 Non-Harmonic and Non-Local Objective Functions

6.4 Identifying Near-Native Structures from Predicted Candidates.

6.4.1 A New Clustering-Based Selection Method

6.4.2 Combined Ranking Method

6.5 Experimental Results

6.6 Summary

References

Brief Introduction of Authors

7 Recursive Nonparametric Discriminant Analysis for Object Detection

7.1 Introduction

7.2 Related Work

7.3 Discriminant Feature Extraction for Object Detection

7.3.1 Fisher Discriminant Analysis and Nonparametric Dis-criminant Analysis

7.3.2 Recursive Nonparametric Discriminant Analysis

7.4 Constructing Classifiers using RNDA Features and AdaBoost

7.4.1 AdaBoost Algorithm

7.4.2 Applying AdaBoost to Combine RNDA Features

7.5 Experiments

7.5.1 Training

7.5.2 Frontal and Profile Face Detection

7.5.3 Eye Detection

7.5.4 Face Recognition Experiments

7.5.5 Discussion on Computational Complexity

7.6 Conclusion

References

Brief Introduction of Authors

8 On the Privacy Preserving Properties of Projection-Based Data Perturbation Techniques

8.1 Introduction

8.2 Perturbation Approaches

8.2.1 Additive-Noise-Based Approach

8.2.2 Distance-Preserving-Based Projection

8.2.3 Non-Distance-Preserving-Based Projection

8.2.4 The General-Linear-Transformation-Based Perturbation

8.3 Direct Attack

8.3.1 ICA Revisited

8.3.2 Drawbacks of Direct ICA

8.4 Sample-Based Attack

8.4.1 Attacks for Distance-Preserving-Based Projection

8.4.2 Attacks for Non-Distance-Preserving-Based Projection

8.4.3 Attacks for General-Linear-Transformation-Based Per-turbation

8.5 Empirical Evaluations

8.5.1 Effect of Noise and the Transformation Matrix

8.5.2 Effect of the Sample Size

……

9 Bayesian Networks Modeling for Software Inspection Effectiveness

10 CI and CFD:integration through Smart Simulations

11 Intelligent Video Content Analysis and Applications

Editors of the Book

内容摘要:

阐述计算智能的理论和相关的应用。重点介绍了如下三个方面的内容:计算智能的前沿技术,可以用计算智能的方法来解决的前沿问题,计算智能的最新技术在相关领域的应用。《计算智能及其应用》可作为信息科学技术领域高年级本科生和研究生的针对计算智能的入门教材,也可以供从事科研和技术开发的人员参考。IEEE计算智能协会是该领域重要学术组织,并为《计算智能及其应用》编写提供很大帮助。

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出版地合肥出版单位中国科学技术大学出版社
版次1版印次1
定价(元)68.0语种英文
尺寸26装帧平装
页数印数

书籍信息归属:

计算智能及其应用是中国科学技术大学出版社于2009.06出版的中图分类号为 TP183 的主题关于 人工智能-神经网络-计算-英文 的书籍。