Systems engineering neural networks / Alessandro Migliaccio, Giovanni Iannone.
By: Migliaccio, Alessandro [author.]
Contributor(s): Iannone, Giovanni [author.]
Language: English Publisher: Hoboken, NJ, USA : Wiley, 2023Description: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781119901990; 9781119902003; 1119902002; 9781119902010Subject(s): Neural networks (Computer science) | Computer simulation | Systems engineeringGenre/Form: Electronic books.Additional physical formats: Print version:: Systems engineering neural networksDDC classification: 006.3/2 LOC classification: QA76.87Online resources: Full text available at Wiley Online Library Click here to view| Item type | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
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COLLEGE LIBRARY | COLLEGE LIBRARY | 006.32 M5882 2023 (Browse shelf) | Available | CL-53759 |
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| 006.32 H17 2001 Principles of neurocomputing for science and engineering / | 006.32 H331 1999 Neural networks : a comprehensive foundation / | 006.32 L7401 2021 Artificial intelligence hardware design : challenges and solutions / | 006.32 M5882 2023 Systems engineering neural networks / | 006.32 Z615 2020 Learning in energy-efficient neuromorphic computing : algorithm and architecture co-design / | 006.33 C234 1989 Building knowledge systems : developing and managing rule-based applications / | 006.33 Ex71 1988 Expert systems : introduction to the technology and applications / |
Includes bibliographical references and index.
Table of Contents
ABOUT THE AUTHORS
ACKNOWLEDGEMENTS 7
HOW TO READ THIS BOOK 8
Part I 9
1 A BRIEF INTRODUCTION 9
THE SYSTEMS ENGINEERING APPROACH TO ARTIFICIAL INTELLIGENCE (AI) 14
SOURCES 18
CHAPTER SUMMARY 18
QUESTIONS 19
2 DEFINING A NEURAL NETWORK 20
BIOLOGICAL NETWORKS 22
FROM BIOLOGY TO MATHEMATICS 24
WE CAME A FULL CIRCLE 25
THE MODEL OF McCULLOCH-PITTS 25
THE ARTIFICIAL NEURON OF ROSENBLATT 26
FINAL REMARKS 33
SOURCES 35
CHAPTER SUMMARY 36
QUESTIONS 37
3 ENGINEERING NEURAL NETWORKS 38
A BRIEF RECAP ON SYSTEMS ENGINEERING 40
THE KEYSTONE: SE4AI AND AI4SE 41
ENGINEERING COMPLEXITY 41
THE SPORT SYSTEM 45
ENGINEERING A SPORT CLUB 51
OPTIMISATION 52
AN EXAMPLE OF DECISION MAKING 56
FUTURISM AND FORESIGHT 60
QUALITATIVE TO QUANTITATIVE 61
FUZZY THINKING 64
IT IS ALL IN THE TOOLS 74
SOURCES 77
CHAPTER SUMMARY 77
QUESTIONS 78
Part II 79
4 SYSTEMS THINKING FOR SOFTWARE DEVELOPMENT 79
PROGRAMMING LANGUAGES 82
ONE MORE THING: SOFTWARE ENGINEERING 94
CHAPTER SUMMARY 101
QUESTIONS 102
SOURCES 102
5 PRACTICE MAKES PERFECT 103
EXAMPLE 1: COSINE FUNCTION 105
EXAMPLE 2: CORROSION ON A METAL STRUCTURE 112
EXAMPLE 3: DEFINING ROLES OF ATHLETES 127
EXAMPLE 4: ATHLETE’S PERFORMANCE 134
EXAMPLE 5: TEAM PERFORMANCE 142
A human-defined-system 142
Human Factors 143
The sport team as system of interest 144
Impact of Human Error on Sports Team Performance 145
EXAMPLE 6: TREND PREDICTION 156
EXAMPLE 7: SYMPLEX AND GAME THEORY 163
EXAMPLE 8: SORTING MACHINE FOR LEGO® BRICKS 168
Part III 174
6 INPUT/OUTPUT, HIDDEN LAYER AND BIAS 174
INPUT/OUTPUT 175
HIDDEN LAYER 180
BIAS 184
FINAL REMARKS 186
CHAPTER SUMMARY 187
QUESTIONS 188
7 ACTIVATION FUNCTION 189
TYPES OF ACTIVATION FUNCTIONS 191
ACTIVATION FUNCTION DERIVATIVES 194
ACTIVATION FUNCTIONS RESPONSE TO W AND b VARIABLES 200
FINAL REMARKS 202
CHAPTER SUMMARY 204
QUESTIONS 205
SOURCES 205
8 COST FUNCTION, BACK-PROPAGATION AND OTHER ITERATIVE METHODS 206
WHAT IS THE DIFFERENCE BETWEEN LOSS AND COST? 209
TRAINING THE NEURAL NETWORK 212
BACK-PROPAGATION (BP) 214
ONE MORE THING: GRADIENT METHOD AND CONJUGATE GRADIENT METHOD 218
ONE MORE THING: NEWTON’S METHOD 221
CHAPTER SUMMARY 223
QUESTIONS 224
SOURCES 224
9 CONCLUSIONS AND FUTURE DEVELOPMENTS 225
GLOSSARY AND INSIGHTS 233
"A complete and authoritative discussion of systems engineering and neural networks In Systems Engineering Neural Networks, a team of distinguished researchers deliver a thorough exploration of the fundamental concepts underpinning the creation and improvement of neural networks with a systems engineering mindset. In the book, you'll find a general theoretical discussion of both systems engineering and neural networks accompanied by coverage of relevant and specific topics, from deep learning fundamentals to sport business applications. Readers will discover in-depth examples derived from many years of engineering experience, a comprehensive glossary with links to further reading, and supplementary online content. The authors have also included a variety of applications programmed in both Python 3 and Microsoft Excel"-- Provided by publisher.
About the Author
Alessandro Migliaccio is a certified systems engineer and member of the INCOSE Artificial Intelligence Working Group. He is a graduate of the Delft University of Technology in Space Engineering, USA, and has second level master’s degree in Robotics and Intelligent Systems.
Giovanni Iannone is a mechanical engineer and a graduate of the University of Naples Federico II. Second level master’s degree in Systems Engineering at Missouri University of Science and Technology, USA. He has been an active member of INCOSE for several years.
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