Spatial Cognitive Engine Technology

1st Edition - June 15, 2023
Authors: Jianjun Zhang, Jing Li
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 9 5 1 0 7 - 4
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 5 8 6 8 - 4

Spatial Cognitive Engine Technology discusses the increase in user demand for satellite wireless communication services that has led to the increasing development of spectr… Read more

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Spatial Cognitive Engine Technology discusses the increase in user demand for satellite wireless communication services that has led to the increasing development of spectrum resources and the fixed spectrum allocation mode which makes the utilization rate of spectrum resources lower. As an intelligent spectrum sharing technology, cognitive radio has innovated the traditional spectrum management system and is one of the effective ways to solve the above-mentioned problems. As the core of satellite cognitive radio, the spatial cognitive engine can use artificial intelligence to dynamically configure working parameters according to changes in the communication environment and user needs.

Cover image
Title page
Table of Contents
Copyright
Preface
Chapter 1. Cognitive radio
1.1. Introduction
1.2. Concept of cognitive radio
1.3. Characteristics of cognitive radio technology
Chapter 2. Cognitive engine technology
2.1. Conceptual connotation of the cognitive engine
2.2. Functions of cognitive engine
2.3. Typical cognitive engine model
Chapter 3. Artificial intelligence technology
3.1. Artificial intelligence concept
3.2. Spacecraft intelligent autonomy level
3.3. Development and direction of artificial intelligence
Chapter 4. Requirements and challenges of space artificial intelligence
4.1. Space system demand for artificial intelligence technology applications
4.2. Challenges to and solutions for application of artificial intelligence in aerospace
Chapter 5. Cognitive engine design based on artificial intelligence
5.1. Artificial intelligence technology at different cognitive stages
5.2. Cognitive engine architecture design based on artificial intelligence technology
5.3. Cognitive engine algorithm design based on artificial intelligence technology
Chapter 6. Typical applications of cognitive engines
6.1. Multiobjective optimization and genetic algorithm
6.2. Design of cognitive engine based on genetic algorithm
6.3. Case reasoning overview
6.4. Case reasoning design in cognitive engine
Chapter 7. Cognitive engine knowledge base design
7.1. Role of knowledge base
7.2. Data table structure design of knowledge base
Chapter 8. Hybrid inference integration mechanism based on data drive
8.1. Hybrid inference integration mechanism based on data drive
8.2. Service-oriented architecture–based inference engine framework design
Chapter 9. Object-oriented knowledge representation
9.1. The data, information, knowledge, wisdom hierarchical model of knowledge
9.2. Concept of knowledge representation
9.3. Object-oriented knowledge representation
Chapter 10. Basic theory and technology of reasoning engine
10.1. Rule-based reasoning
10.2. Case reasoning
10.3. Comparison between rule-based reasoning and case-based reasoning
10.4. Distributed technology
Chapter 11. Spacecraft
11.1. Overview
11.2. Satellite remote sensing
11.3. Satellite communications
11.4. Satellite navigation
Chapter 12. Compound knowledge mining
12.1. Data mining
12.2. Text mining
12.3. Summary of chapter
Chapter 13. Machine learning algorithm for cognitive engine
13.1. Artificial intelligence: endowing human intelligence to machines
13.2. Machine learning: a method to realize artificial intelligence
13.3. Deep learning: a technology to realize machine learning
13.4. Reinforcement learning: self-evolution mechanism of learning feedback
13.5. Transfer learning is a machine learning method that uses existing knowledge to solve problems in different but related fields
13.6. Key technologies of artificial intelligence
13.7. Analysis of technology development trends
13.8. Machine learning
Chapter 14. Intelligent language knowledge for cognitive engine
14.1. Natural language processing
14.2. Knowledge engineering
Index

Jianjun Zhang

Jianjun Zhang, PhD, is a Professor at the Beijing Institute of Spacecraft System Engineering, China Academy of Space Technology, Member of the Youth Science Club of China Electronics Society, Member of the Edge Computing Expert of China Electronics Society, Chairman of the "Space (Aerospace) Information Technology," Professional Committee of China Electronics Society, and Member of the Satellite Application Expert Group of China Aerospace Society. He mainly engaged in satellite navigation system design and advanced spatial information system technology based on cognitive mechanism. He has presided over several major projects such as the National Natural Science Foundation's major research project, the final assembly fund, the 863 project, and the development project of the Science and Technology Commission of the China Academy of Space Technology. He has published more than 50 SCI/EI research papers in international journals and conferences, authorized more than 20 invention patents at home and abroad, and published 3 monographs. He won third prize of the National Defense Science and Technology Progress Award.

Affiliations and expertise

Professor, China Academy of Space Technology, Beijing, China

Jing Li

Jing Li, Ph.D., is an Associate Professor at the School of Automation, Beijing Institute of Technology. Expert member of the “Space Information Technology” Youth Committee of China Electronics Society, the main research direction is robot environmental awareness, image detection and target tracking, multi-sensor information fusion. She has presided over more than 10 projects including the National Natural Science Youth Fund, the Postdoctoral Special Fund, the Key Laboratory of the Ministry of Education, and the Science and Technology Cooperation. She has published 25 academic papers (including 10 SCI papers and 15 EI papers) and the book "Image Detection and Object Tracking Technology", granted 7 national invention patents as the first author and the National Science and Technology Progress Award 2 (ranked 8th).

Affiliations and expertise

Associate Professor, Beijing Institute of Technology, China