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KAM : a system for intelligently guiding numerical experimentation by computer

Author: Kenneth Man-Kam Yip
Publisher: Cambridge, Mass. : MIT Press, ©1991.
Series: Artificial intelligence (Cambridge, Mass.)
Edition/Format:   Print book : EnglishView all editions and formats
Summary:

Graphical representations are often used as parts of the process of solving verbally presented problems. Yip shows how to automate key aspects of this style of reasoning, demonstrating the  Read more...

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Additional Physical Format: Online version:
Yip, Kenneth Man-Kam.
KAM.
Cambridge, Mass. : MIT Press, ©1991
(OCoLC)555787301
Document Type: Book
All Authors / Contributors: Kenneth Man-Kam Yip
ISBN: 0262240343 9780262240345
OCLC Number: 23765707
Description: xvi, 242 pages : illustrations ; 24 cm.
Contents: Part 1 Introduction: goal - automate part of a scientist's work; Henon's area preserving map - an illustration; what KAM does; how KAM does it; what does KAM build on?; the rest of the story. Part 2 Overview of KAM: a session with KAM; design criteria; KAM overview - structure and processes. Part 3 Orbit recognition: what is orbit recognition?; core idea - shape from minimal spanning trees; implementation; experiment - main illustration; another experiment - orbit on the surface of a Torus; evaluating the performance. Part 4 Phase space searching: what is phase space searching?; core idea - consistency of neighbouring orbits; rotation number - continuity of discrete flows; orbit compatibility; implementation; experiment - main illustration; other experiments; a concise phase portrait description; evaluating the performance. Part 5 Parameter space searching: what are bifurcations? core idea - structural stability; generic bifurcations of fixed points; phase portrait compatibility; implementation; experiment; evaluating the performance; executive summary of numerical experiments. Part 6 Exploring an open problem: scenario; standing waves in a rectangular tank; mathematical formulation; numerical findings - making a Poincare section; applying an analytical approximation method; comparing analytical predictions with numerical findings; how physical parameters affect chaos; what have we learned? Part 7 Conclusion: what does KAM do?; why does KAM work?; what are the contributions; what's next - enhancing KAM, a workbench approach to scientific computing; user manual. (Part contents).
Series Title: Artificial intelligence (Cambridge, Mass.)
Responsibility: Kenneth Man-Kam Yip.

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