Artificial intelligence in geography:
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Chichester [u.a.]
Wiley
1997
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007703489&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XV, 329 S. graph. Darst., Kt. |
| ISBN: | 0471969915 |
Internformat
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Datensatz im Suchindex
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|---|---|
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| adam_text | Artificial Intelligence
in Geography
Stan Openshaw
University of Leeds, UK
and
Christine Openshaw
University of Sheffield, UK
JOHN WILEY amp; SONS
Chichester • New York • Weinheim • Brisbane * Singapore • Toronto
Contents
Foreword xiii
Acknowledgements xvii
CHAPTER 1 Artificial intelligence and geography
1 1 An emerging crisis in a world full of dumb computer systems
and non-smart analysis and modelling tools 1
1 2 AI is important to geography 6
1 3 Why AI is so important to human geography 9
1 4 So what do geographers need to know about AI? 12
1 5 What is AI? 13
^16 Can machines think? 20
1 7 AI is widely viewed as being future essential 22
1 8 What does AI consist of? 23
1 9 AI is a future essential toolkit for geography 24
1 10 Questions and Answers 26
Appendix 1 Structure of the Introduction to the AI Course in the
School of Geography, University of Leeds 29
References 31
CHAPTER 2 A brief history of artificial intelligence
2 1 Historical overview 33
2 2 The early years, 1930s and 1940s 34
2 3 The first neural nets era: 1950-1970 35
2 4 Heuristic search in the 1960s and 1970s 37
2 5 Knowledge-based systems 1970-1980s 37
2 6 Neural nets 2: 1986 onwards 39
2 7 Evolutionary programming and artificial life 39
2 8 Fuzzy Logic and Hybrid Intelligent Systems 40
2 9 Into an Al-rich and increasingly Al-dependent future 41
2 10 What might geographers expect from AI? 43
2 11 Principal geographical applications of AI 44
viii CONTENTS
2 12 Conclusions 49
2 13 Questions and Answers 49
References 51
CHAPTER 3 Heuristic search in geography
3 1 Playing games 55
311 Spatial search 57
3 2 Heuristic search methods of the traditional AI kind 59
3 3 Some illustrations of heuristic search 63
3 4 Heuristic search to optimise a function 64
3 5 Some applications of blind search in geography 72
351 Case study 1: finding nuclear power station sites 73
352 Case study 2: an optimal nuclear bombing strategy 77
353 Making spatial searching more intelligent 77
354 Map searching as a parallel process 80
3 6 More sophisticated examples of heuristic search 82
361 Case study 3: spatial network optimisation 82
362 Case study 4: zone design 83
3 7 Exploratory spatial analysis as a map search process 87
371 Case study 5: the geographical analysis machine 87
372 Case study 6: the geographical correlates exploration
machine 91
3 8 Conclusions 94
3 9 Questions and Answers 96
Appendix 1 A simple Monte Carlo search procedure 102
Appendix 2 A simple Monte Carlo focused search for numerical
optimization 103
Appendix 3 A simple Monte Carlo focused search heuristic
suitable for zone design 104
Appendix 4 A simulated annealing search procedure 104
Appendix 5 A tabu search procedure 105
References 106
CHAPTER 4 Expert systems and intelligent knowledge-based systems
4 1 Introduction 108
4 2 Definitions of expert systems 110
4 3 What are expert systems so potentially useful? I l l
4 4 What is an intelligent knowledge-based system? 113
4 5 What does a simple ES consist of? 114
4 6 Building a simple expert system 116
461 The knowledge base (rule base) 116
4A2 The inference engine 117
463 Handling uncertainty 118
CONTENTS ix
464 Knowledge acquisition and knowledge engineering 119
465 Some ethical issues 119
4 7 Geographic examples of expert systems 120
4 8 Automatic rule making from examples 122
481 Knowledge discovery systems 123
482 Memory-based reasoning (MBR) 124
4 9 Other types of intelligent knowledge-based systems 128
4 10 Conclusions 129
4 11 Questions and Answers 131
References 135
CHAPTER 5 Neurocomputing
5 1 Introduction 137
511 Solving problems that were previously impossible 139
5 2 So what is a neural net? 141
53A brief look at the history of neural nets 146
531 The first neural networks 1943-69 146
532 The years of gloom and dormancy: 1969-82 147
533 The new neural nets: 1982-86 148
534 Take off: 1987- 148
535 The promise of neurocomputing 149
54A geographical appreciation 150
5 5 What are the potential neural network modelling applications
k
in geography? 154
5 6 Conclusions 156
5 7 Questions and Answers 157
References 161
CHAPTER 6 Applying artificial neural networks
6 1 Introduction 163
6 2 Supervised neural networks 164
621 The black box 164
622 How does it work? 167
623 Pros and cons 174
624 Spatial interaction modelling using a neural net 174
625 Neural net modelling of telecommunication flows 177
626 Try it out! * 178
627 Some neural benefits 178
6 3 Unsupervised neural networks 179
631 Unsupervised training 179
632 Review of potential neuroclassifier architectures 181
633 Comparisons with conventional classifiers 184
x CONTENTS
634 Kohonen s self-organising maps as the basis for a spatial data
classifier 185
635 Kohonen s self-organising map as a modeller 189
636 Some empirical evaluations and case studies 190
6 4 Conclusions 192
6 5 Questions and Answers 193
References 198
CHAPTER 7 Evolutionary computation, genetic algorithms, evolution
strategies and genetic programming
7 1 Introduction 201
7 2 Genetic algorithms 202
721 What is a genetic algorithm? 202
722A basic genetic algorithm 204
723 So how does the genetic algorithm work? 207
724 Genetic algorithm problems and advantages 208
7 3 Other types of evolution programming 210
731 Non-binary genetic algorithms 210
732 Evolution strategies 210
733 An empirical comparison of evolutionary strategies with
genetic algorithms 212
7 4 Building model breeding machines 216
741 Background 216
742 Model breeding: modelling census relationships 217
743 Model breeding: building spatial interaction models 220
744 Model breeding problems 221
7 5 Genetic programming and evolving computer programs 222
751A basic algorithm for genetic programming 222
f752 An example of genetic programming 224
753 More algorithmic details 224
754 Goods and bads 225
76A genetic programming approach to building new spatial
interaction models
7 7 Conclusions
7 8 Questions and Answers
References
CHAPTER 8 Artificial life
8 1 Introduction
8 2 What is artificial life?
8 3 Why is artificial life an important technology?
8 4 Primitive artificial life
841 Cellular automaton
CONTENTS xi
842A one-dimensional or linear cellular automaton 242
843 Two-dimensional cellular automaton 244
844 Cellular automaton as a modelling tool 247
845 Building artificial bugs 248
8 5 Some examples of artificial life in GIS 251
851 MAPEX 251
852 More sophisticated GIS trispace explorers 255
853 Some other possibilities 261
854 Distributed AI 261
8 6 Conclusions 262
8 7 Questions and Answers 263
References 266
CHAPTER 9 Fuzzy logic, fuzzy systems and soft computing
9 1 Why it is important? 268
9 2 What is fuzzy logic? 270
921 We live in a fuzzy word 270
922 So what is fuzzy set theory? 271
923 Fuzziness versus probability 278
9 3 Building a fuzzy systems model 279
931 When might this be useful? 279
932 Fuzzy spatial interaction modelling 301
9 4 Conclusions 301
941 Fuzzy modelling is in principle simple 301
942 Some advantages 302
943 Some disadvantages 302
944 So what! 303
9 5 Questions and Answers 304
References 307
CHAPTER 10 Conclusions and epilogue
10 1 An emerging era of the smart machine 309
10 2 Geographical hopes 311
10 3 Doubts and questions 312
10 4 A research agenda 314
10 4 1 AI in spatial analysis relevant to GIS 314
10 4 2 Spatial modelling in GIS 315
10 4 3 Applications in human geography 315
10 4 4 New applications 316
10 4 5 Real-world demonstrators 316
10 4 6 Teaching 317
10 4 7 Social consequences 317
10 4 8 Geocomputation 317
xii CONTENTS
10 5 Conclusions 317
10 6 Questions and Answers 318
References 319
Index 321
|
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| discipline | Informatik Geographie |
| format | Book |
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| indexdate | 2024-12-20T10:12:45Z |
| institution | BVB |
| isbn | 0471969915 |
| language | English |
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| spellingShingle | Openshaw, Stan Openshaw, Christine Artificial intelligence in geography Geografie gtt Géomatique Géomatique ram Intelligence artificielle Intelligence artificielle ram Kunstmatige intelligentie gtt Datenverarbeitung Geografie Künstliche Intelligenz Artificial intelligence Geography Data processing Geografie (DE-588)4020216-1 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd |
| subject_GND | (DE-588)4020216-1 (DE-588)4033447-8 |
| title | Artificial intelligence in geography |
| title_auth | Artificial intelligence in geography |
| title_exact_search | Artificial intelligence in geography |
| title_full | Artificial intelligence in geography Stan Openshaw and Christine Openshaw |
| title_fullStr | Artificial intelligence in geography Stan Openshaw and Christine Openshaw |
| title_full_unstemmed | Artificial intelligence in geography Stan Openshaw and Christine Openshaw |
| title_short | Artificial intelligence in geography |
| title_sort | artificial intelligence in geography |
| topic | Geografie gtt Géomatique Géomatique ram Intelligence artificielle Intelligence artificielle ram Kunstmatige intelligentie gtt Datenverarbeitung Geografie Künstliche Intelligenz Artificial intelligence Geography Data processing Geografie (DE-588)4020216-1 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd |
| topic_facet | Geografie Géomatique Intelligence artificielle Kunstmatige intelligentie Datenverarbeitung Künstliche Intelligenz Artificial intelligence Geography Data processing |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007703489&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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