Fuzzy Logic in Geology

Front Cover
Robert V. Demicco, George J. Klir
Elsevier, Oct 20, 2003 - Computers - 347 pages
What is fuzzy logic?--a system of concepts and methods for exploring modes of reasoning that are approximate rather than exact. While the engineering community has appreciated the advances in understanding using fuzzy logic for quite some time, fuzzy logic's impact in non-engineering disciplines is only now being recognized. The authors of Fuzzy Logic in Geology attend to this growing interest in the subject and introduce the use of fuzzy set theory in a style geoscientists can understand. This is followed by individual chapters on topics relevant to earth scientists: sediment modeling, fracture detection, reservoir characterization, clustering in geophysical data analysis, ground water movement, and time series analysis.


George Klir is the Distinguished Professor of Systems Science and Director of the Center for Intelligent Systems, Fellow of the IEEE and IFSA, editor of nine volumes, editorial board member of 18 journals, and author or co-author of 16 books

Foreword by the inventor of fuzzy logic-- Professor Lotfi Zadeh
 

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Contents

An Overview
63
A Literature Review
103
Chapter 5 Applications of Fuzzy Logic to Stratigraphic Modeling
121
Chapter 6 Fuzzy Logic in Hydrology and Water Resources
153
Chapter 7 Formal Concept Analysis in Geology
191
Chapter 8 Fuzzy Logic and Earthquake Research
239
Application to the Reef Growth Problem
275
Chapter 10 Ancient Sea Level Estimation
301
Acknowledgments
337
Index
339
Color Plates Section
348
Copyright

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Page 17 - F, where X and Y are crisp sets, we say that the function is fuzzified when it is extended to act on fuzzy sets defined on X and Y. That is, the fuzzified function maps, in general, fuzzy sets defined on X to fuzzy sets defined on Y. Formally, the fuzzified function, F, has the form...
Page x - Computing with words (CW) is inspired by the remarkable human capability to perform a wide variety of physical and mental tasks without any measurements and any computations. Familiar examples of such tasks are parking a car, driving in heavy traffic, playing golf, riding a bicycle, understanding speech, and summarizing a story.
Page 12 - Contrary to the classical concept of a set, or crisp set, the boundary of a fuzzy set is not precise. That is, the change from nonmembership to membership in a fuzzy set is gradual rather than abrupt. This gradual change is expressed by a membership grade function...
Page x - No doubt Professor Zadeh's enthusiasm for fuzziness has been reinforced by the prevailing political climate in the US one of unprecedented permissiveness *. " Fuzzification " is a kind of scientific permissiveness; it tends to result in socially appealing slogans unaccompanied by the discipline of hard scientific work and patient observation. I must confess that I cannot conceive of
Page x - What we need is more logical thinking, not less. The danger of fuzzy theory is that it will encourage the sort of imprecise thinking that has brought us so much trouble.
Page x - I would like to comment briefly on Professor Zadeh's presentation. His proposals could be severely, ferociously, even brutally criticized from a technical point of view. This would be out of place here. But a blunt question remains: Is Professor Zadeh presenting important ideas or is he indulging in wishful thinking? No doubt Professor Zadeh's enthusiasm for fuzziness has been reinforced by the prevailing climate in the US — one of unprecedented permissiveness. 'Fuzzification...

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