数据驱动的信息物理系统（英文版）

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作　者：	李方昱、伍小龙、韩红桂
出版社：	清华大学出版社
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标　签：	暂缺

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ISBN：	9787302669388	出版时间：	2024-08-01	包装：	平装-胶订
开本：	16开	页数：		字数：

内容简介

　　《数据驱动的信息物理系统（英文版）》聚焦于数据驱动CPS系统的原则、设计和实现，涵盖了数据采集、分析和建模、机器学习和人工智能、网络与分布式计算以及网络安全等主题。《数据驱动的信息物理系统（英文版）》全面介绍了开发数据驱动信息物理系统所使用的最先进的技术和方法，以及它们在制造业、医疗保健、交通运输和能源等各个行业中的应用。

作者简介

　　李方昱，北京工业大学教授，博士生导师，国家海外优青、国家重点研发计划青年科学家，长期致力于数据驱动的复杂系统模型构建与分析研究，主持国家重点研发计划项目、国家自然科学基金面上项目多项，在权威国际期刊上发表SCI论文90余篇，ESI高被引论文3篇，入选斯坦福全球前2%顶尖科学家榜单。伍小龙，北京工业大学副教授，硕士生导师。从事大数据分析、人工神经网络设计、智能特征建模、智能控制等方向的研究。曾获中国自动化学会优秀博士学位论文奖，中国自动化科技进步一等奖，中国发明协会创业奖×创新奖一等奖，曾在国内外期刊及会议上发表学术论文30余篇，参与撰写专著2本，现任中国自动化学会青年工作委员会委员，中国环境感知与保护自动化委员会委员。韩红桂，北京工业大学教授，博士生导师，国家重点研发计划项目首席科学家、国家自然科学基金杰出青年科学基金项目获得者、国家自然科学基金优秀青年科学基金项目获得者、中国自动化学会青年科学家，长期从事复杂系统智能优化运行控制理论方法和关键技术的研究。现任“数字社区”工程研究中心主任、“计算智能与智能系统”北京市重点实验室主任等，兼任中国自动化学会环保自动化专业委员会秘书长、中国自动化学会过程控制专业委员会委员。

图书目录

Chapter 1 Introduction to Data-driven Cyber Physical Systems 1
1.1 What are cyber physical systems? 2
1.2 Data-driven approaches for CPS 3
1.3 Importance of DDCPS 3
1.4 Key challenges in DDCPS 4
1.5 Applications of DDCPS 11
1.6 Evolution of data-driven approaches in cyber physical systems 12
1.7 How can data be used to improve cyber physical systems? 15
1.8 Overview of the book 18
References 18
Chapter 2 Fundamentals of Data-driven Cyber Physical Systems 20
2.1 Definitions 20
2.1.1 Definitions of CPS 20
2.1.2 Definitions of DDCPS 31
2.2 Characteristics of DDCPS 34
2.2.1 Networked communication 35
2.2.2 Scalability 36
2.2.3 Heterogeneity 38
2.2.4 Interdisciplinary 39
2.2.5 Real-time processing 40
2.2.6 Real-time decision-making 41
2.3 Components of DDCPS 41
2.3.1 Sensing components 41
2.3.2 Computational components 42
2.3.3 Communication components 43
2.3.4 Control components 44
2.4 Examples of DDCPS in different industries 45
2.4.1 Smart grids 45
2.4.2 Agriculture 46
2.4.3 Healthcare 47
2.4.4 Intelligent transportation 49
2.4.5 Smart manufacturing 51
2.5 Challenges of DDCPS 53
2.5.1 Data storage 54
2.5.2 Integration 55
2.5.3 Communication 56
2.5.4 Cybersecurity 57
2.5.5 System stability 58
2.6 Summary 60
References 60
Chapter 3 Data Collection in Cyber Physical Systems 66
3.1 Sensors and auxiliary components 66
3.1.1 Type of sensor and auxiliary components 67
3.1.2 Factors for selecting sensors and auxiliary components 71
3.1.3 Typical scenarios for data collection 75
3.2 Types of data 79
3.2.1 One dimensional data 81
3.2.2 Image and video data 83
3.2.3 Other types of data 85
3.3 Real time and latency 87
3.3.1 Techniques for reducing latency 88
3.3.2 Key considerations of real time and latency 92
3.3.3 Evaluating the performance 95
3.4 Data quality and reliability issues 98
3.4.1 Data preprocessing techniques 100
3.4.2 Impact of data redundancy on reliability 103
3.4.3 Data validation techniques 104
3.5 Summary 107
References 108
Chapter 4 Data Storage and Management in Cyber Physical Systems 115
4.1 Types of data storage for DDCPS 116
4.1.1 An introduction to data storage in DDCPS 116
4.1.2 Explore data storage instances in the system 128
4.2 Data management and processing techniques 131
4.2.1 Database management techniques 133
4.2.2 Data processing techniques 137
4.3 Big data processing technology of DDCPS 140
4.3.1 Data process for storage and management 141
4.3.2 Storage for DDCPS 141
4.3.3 Management for DDCPS 143
4.3.4 Big data for DDCPS 144
4.4 Summary 144
References 145
Chapter 5 Data Integration and Fusion in Cyber Physical Systems 153
5.1 Data integration and fusion 153
5.1.1 CPS data characteristics 154
5.1.2 CPS data integration 155
5.1.3 CPS data fusion 156
5.1.4 Data integration and fusion framework 157
5.1.5 Data representation 160
5.2 Techniques for fusing data from multiple sources 161
5.2.1 Stage-based data fusion methods 161
5.2.2 Semantic meaning-based data fusion 163
5.2.3 Artificial intelligence-based data fusion 170
5.3 CPS data integration and fusion case studies 173
5.3.1 Cloud-integrated CPS for smart cities case study 173
5.3.2 Data fusion framework for smart healthcare case study 175
5.4 Challenges and future work opportunities 179
5.4.1 Integrated models challenges 179
5.4.2 CPS data fusion challenges 181
5.4.3 Future work opportunities 185
5.5 Summary 187
References 188
Chapter 6 Data-driven Modeling and Simulation in Cyber Physical Systems 194
6.1 Importance of modeling and simulation in cyber physical systems 195
6.1.1 Importance of complex system modeling for CPS 197
6.1.2 Importance of complex system simulation for CPS 200
6.1.3 Benefits of modeling and simulation in CPS 203
6.2 Data-driven modeling techniques 205
6.2.1 Introduction to data-driven modeling 207
6.2.2 Types of data-driven models used in CPS 210
6.2.3 Methods for model selection and validation 226
6.2.4 Examples of data-driven modeling in CPS applications 229
6.3 Simulation and testing of cyber physical systems using data-driven models 230
6.3.1 Introduction to data-driven simulation 232
6.3.2 Types of data-driven simulation used in CPS 234
6.3.3 Model validation and uncertainty quantification 237
6.3.4 Case studies of simulation and testing using data-driven models in CPS
applications 238
6.4 Summary 240
References 241
Chapter 7 Fault Detection and Predictive Maintenance in Cyber Physical
Systems 247
7.1 An overview of fault detection and maintenance 247
7.1.1 The development of CPS fault detection 248
7.1.2 The development of CPS maintenance 250
7.1.3 Future trends of fault detection and predictive maintenance 251
7.2 Data-driven approaches for fault detection and predictive maintenance 253
7.2.1 Data-driven fault detection approaches 254
7.2.2 Data-driven predictive maintenance approaches 259
7.2.3 Discussion of fault detection and predictive maintenance 264
7.3 Applications of fault detection and predictive maintenance 266
7.3.1 Application background of fault detection and predictive maintenance 267
7.3.2 Case studies of fault detection and predictive maintenance 273
7.3.3 Challenges in cases 283
7.4 Summary 285
References 285
Chapter 8 Cybersecurity in Data-driven Cyber Physical System 291
8.1 Cyber attacks in data-driven CPS 293
8.1.1 Attacks at the perception layer 294
8.1.2 Attacks at the transmission layer 297
8.1.3 Attacks at the platform layer 299
8.1.4 Attacks at the application layer 301
8.2 Requirements of cybersecurity 302
8.2.1 Objective of cybersecurity 302
8.2.2 Hardware security 303
8.2.3 Software security 305
8.2.4 Network security 306
8.2.5 Data security 307
8.3 Importance of cybersecurity in data-driven CPS 308
8.3.1 Data integrity and accuracy 309
8.3.2 Privacy and confidentiality 310
8.3.3 System resilience and availability 311
8.3.4 Regulatory requirements 313
8.4 Challenges of cybersecurity in data-driven CPS 314
8.4.1 Data-driven techniques for attack detection and mitigation 314
8.4.2 Data trustworthiness and policy-based sharing 316
8.4.3 Risk-based security metrics 317
8.5 Data-driven techniques of cybersecurity in CPS 318
8.5.1 Data-driven attack detection and migitation 319
8.5.2 Data-driven data confidence assessment 330
8.5.3 Risk assessment metrics 332
8.6 Summary 334
References 334
Chapter 9 Future of Data-driven Cyber Physical Systems 345
9.1 Potential impacts 345
9.2 Emerging trends and technologies in DDCPS 349
9.3 Societal and ethical implications 351
9.4 Concluding remarks 353
Acknowledgements 355