"Fuzzy Logic in Geology" Ed. by Robert V. Demicco, George J. Klir
Elsevier Academic Press | 2004 | ISBN: 0124151469 | 366 pages | PDF | 5 Mb
Elsevier Academic Press | 2004 | ISBN: 0124151469 | 366 pages | PDF | 5 Mb
Fuzzy Logic in Geology is a true role model. It is a high quality work which opens the door to application of new methods and new viewpoints to a variety of basic problems in geology, geophysics, and related fields. It is well-organized and reader-friendly.
This book has three purposes. Its first purpose is to demonstrate that fuzzy logic opens a radically new way to represent geological knowledge and to deal with geological problems, and that this new approach has been surprisingly successful in many areas of geology. The second purpose is to help geologists understand the main facets of fuzzy logic and the role of these facets in geology. The final purpose of this book is to make researchers in fuzzy logic aware of the emerging opportunities for the application of their expertise in geology.
There is an enormous literature on perceptions, spanning psychology, philosophy, linguistics, and other fields. But what has not been in existence is a theory in which perceptions can be operated on as objects of computation.
Fuzzy logic provides a basis for such a theory—a theory which is referred to as the computational theory of perceptions (CTP).
In the computational theory of perceptions, perceptions are dealt with not as patterns of brain activity, but through their descriptions in a natural language. In this sense, a natural language may be viewed as a system for describing perceptions. Thus, if classical, bivalent logic is viewed as the logic of measurements, then fuzzy logic may be viewed as the logic of perceptions.
Although the methodology of computing with words and perceptions is not treated explicitly in the book, the basic ideas which underlie it are in evidence throughout.
Furthermore, Fuzzy Logic in Geology ventures beyond well-established techniques and presents authoritative expositions of methods which lie on the frontiers of fuzzy logic.
Lotfi A. Zadeh, May 13, 2003, Berkeley, CA
TOC
1 Introduction
2 Fuzzy Logic: A Specialized Tutorial
3 Fuzzy Logic and Earth Science: An Overview
4 Fuzzy Logic in Geological Sciences: A Literature Review
5 Applications of Fuzzy Logic to Stratigraphic Modeling
6 Fuzzy Logic in Hydrology andWater Resources
7 Formal Concept Analysis in Geology
8 Fuzzy Logic and Earthquake Research
9 Fuzzy Transform: Application to the Reef Growth Problem
10 Ancient Sea Level Estimation
There is an enormous literature on perceptions, spanning psychology, philosophy, linguistics, and other fields. But what has not been in existence is a theory in which perceptions can be operated on as objects of computation.
Fuzzy logic provides a basis for such a theory—a theory which is referred to as the computational theory of perceptions (CTP).
In the computational theory of perceptions, perceptions are dealt with not as patterns of brain activity, but through their descriptions in a natural language. In this sense, a natural language may be viewed as a system for describing perceptions. Thus, if classical, bivalent logic is viewed as the logic of measurements, then fuzzy logic may be viewed as the logic of perceptions.
Although the methodology of computing with words and perceptions is not treated explicitly in the book, the basic ideas which underlie it are in evidence throughout.
Furthermore, Fuzzy Logic in Geology ventures beyond well-established techniques and presents authoritative expositions of methods which lie on the frontiers of fuzzy logic.
Lotfi A. Zadeh, May 13, 2003, Berkeley, CA
TOC
1 Introduction
2 Fuzzy Logic: A Specialized Tutorial
3 Fuzzy Logic and Earth Science: An Overview
4 Fuzzy Logic in Geological Sciences: A Literature Review
5 Applications of Fuzzy Logic to Stratigraphic Modeling
6 Fuzzy Logic in Hydrology andWater Resources
7 Formal Concept Analysis in Geology
8 Fuzzy Logic and Earthquake Research
9 Fuzzy Transform: Application to the Reef Growth Problem
10 Ancient Sea Level Estimation
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