Suchen und Finden
Hagenberg Research
von: Bruno Buchberger, Michael Affenzeller, Alois Ferscha, Michael Haller, Tudor Jebelean, Erich Peter Kl
Springer-Verlag, 2009
ISBN: 9783642021275 , 488 Seiten
Format: PDF
Kopierschutz: Wasserzeichen
Preis: 149,79 EUR
Contents
5
Acknowledgement
8
Hagenberg Research: Introduction
9
References
12
Chapter I Algorithms in Symbolic Computation
13
1 The Renaissance of Algorithmic Mathematics
14
1.1 A Bit of History
14
2 Gröbner Bases Theory for Nonlinear Polynomial Systems
24
2.1 The Relevance of Gröbner Bases Theory
24
2.2 Gröbner Bases: Basic Notions and Results
27
3 Rational Algebraic Curves – Theory and Application
32
3.1 What is a Rational Algebraic Curve?
32
3.3 Proper Parametrizations
34
3.4 A Parametrization Algorithm
35
3.5 Applications of Curve Parametrization
38
4 Computer Generated Progress in Lattice Paths Theory
41
4.1 Paths in the Quarter Plane
41
4.2 Computer Algebra Support
43
4.3 Gessel’s Conjecture
44
4.4 Lattice Paths in 3D
46
5 Symbolic Summation in Particle Physics
48
5.1 The Underlying Summation Principles
49
5.2 Example 1: Simplification of Multi-Sums
52
5.3 Example 2: Solving Large Recurrence Relations
55
6 Nonlinear Resonance Analysis
57
6.1 What is Resonance?
57
6.2 Kinematics and Dynamics
60
6.3 Highlights of the Research on the NRA
64
References
66
Chapter II Automated Reasoning
71
1 Introduction
71
2 Theorema: Computer-Supported Mathematical Theory Exploration
73
2.1 The Theorema Language and the User Interface
75
2.2 “Lazy Thinking”: Invention by Formulae Schemes and Failing Proof Analysis
78
3 Natural Style Proving in Theorema
82
3.1 S-Decomposition and the Use of Algebraic Techniques
83
3.2 The Theorema Set Theory Prover
88
4 Unification
91
4.1 General Sequence Unification
91
4.2 Flat Matching
93
4.3 Context Sequence Matching
95
4.4 Relations between Context and Sequence Unification
95
5 Program Verification
96
5.1 Some Principles of Program Verification
97
5.2 Verification of Functional Programs
98
References
106
Chapter III Metaheuristic Optimization
110
1 Introduction
110
1.1 Motivation and Goal
110
1.2 Structure and Content
115
2 Metaheuristic Optimization Techniques
116
2.1 Simulated Annealing
117
2.2 Tabu Search
118
2.3 Iterated Local Search
120
2.4 Evolutionary Algorithms
121
2.5 Scatter Search
122
2.6 Further Metaheuristics
123
2.7 Hybrid Metaheuristics
124
3 Algorithmic Advances Based Upon Genetic Algorithms
125
3.1 The Unique Selling Points of Genetic Algorithms
125
3.2 Schema Theorem and Building Block Hypothesis
126
3.3 Stagnation and Premature Convergence
128
3.4 Offspring Selection (OS)
130
3.5 Consequences Arising out of O spring Selection
133
4 Route Planning
135
4.1 The Vehicle Routing Problem
137
4.2 Heuristic algorithms
140
4.3 Metaheuristic Approaches
141
5 Genetic Programming Based System Identification
143
5.1 Genetic Programming
143
5.2 Data Based Modeling and Structure Identification
146
5.3 Application Example: Time Series Analysis
148
5.4 Application Example: Solving Classification Problems
150
5.5 Analysis of Population Dynamics in Genetic Programming
152
5.6 Data Mining and Genetic Programming
153
6 Conclusion and Future Perspectives
155
References
157
Chapter IV Software Engineering – Processes and Tools
163
1 Introduction
163
2 Software Process Engineering
165
2.1 Concepts Related to Software Process Engineering
168
2.2 Software Process Engineering Research Challenges and Application-oriented Research at SCCH
176
3 Software Quality Engineering
190
3.1 Concepts and Perspectives in Engineering of Software Quality
191
3.2 Management and Automation of Software Testing
194
4 Software Architecture Engineering
206
4.1 General Research Areas and Challenges
207
4.2 Software Architecture Management – Languages and Tools
210
4.3 Software Architectures for Industrial Applications
216
5 Domain-Specific Languages and Modeling
220
5.1 Overview of the Field
221
5.2 Modeling and Code Generation
224
5.3 Textual Domain-Specific Languages
228
5.4 End-User Programming
229
References
232
Chapter V Data-Driven and Knowledge-Based Modeling
242
1 Introduction
242
2 Fuzzy Logics and Fuzzy Systems
243
2.1 Motivation
243
2.3 Fuzzy Systems
244
3 Data-Driven Fuzzy Systems
247
3.1 Motivation
247
3.2 Data-Driven Fuzzy Modeling Approaches
248
3.3 Regularization and Parameter Selection
252
4 Evolving Fuzzy Systems and On-line Modeling
253
4.1 Motivation and Solutions
253
4.2 The FLEXFIS Family
255
4.3 Handling Drifts and Unlearning E ect in Data Streams
259
5 Creating Comprehensible Fuzzy Regression Models
260
5.1 Motivation
260
5.2 The Underlying Language
260
5.3 Rule Induction
262
5.4 Post-Optimization of Fuzzy Rule Bases
264
6 Support Vector Machines and Kernel-Based Design
265
6.1 Kernels as Similarities: Motivation and Recent Developments
265
6.2 Support Vector Machines
267
7 Applications
269
7.1 On-Line Fault Detection at Engine Test Benches
269
7.2 On-Line Image Classification in Surface Inspection Systems
272
7.3 Application of SVMs to Texture Analysis
276
Acknowledgements
278
References
278
Chapter VI Information and Semantics in Databases and on the Web
285
1 Introduction
285
2 Ontologies
287
3 Semantic Networks
293
4 Adaptive Modeling
298
5 Web Information Extraction
304
6 Similarity Queries and Case Based Reasoning
323
7 Data Warehouses
330
References
333
Chapter VII Parallel, Distributed, and Grid Computing
336
1 Introduction
336
2 Parallel Symbolic Computation
345
3 Grid Computing
352
4 GPU Computing for Computational Intelligence
369
References
377
Chapter VIII Pervasive Computing
382
1 What is Pervasive Computing?
383
2 Ensembles of Digital Artifacts
385
3 Quantitative Space: Zones-of-Influence
393
4 Qualitative Space: Spatiotemporal Relations
397
5 Middleware for Space Awareness
405
6 Embodied Interaction
411
7 Outlook
424
References
428
Chapter IX Interactive Displays and Next-Generation Interfaces
435
1 Interactive Surfaces
437
2 Design Challenges
443
3 Design and Implementation of a Multi-Display Environment for Collaboration
455
4 Conclusions
470
References
471
Index
475
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