Knowledge-Driven and Data-Driven Fuzzy Models for Predictive Mineral Potential Mapping

In this paper, we describe new fuzzy models for predictive mineral potential mapping: (1) a knowledge-driven fuzzy model that uses a logistic membership function for deriving fuzzy membership values of input evidential maps and (2) a data-driven model, which uses a piecewise linear function based on...

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Bibliographic Details
Published in:	Natural resources research (New York, N.Y.) Vol. 12; no. 1; pp. 1 - 25
Main Authors:	Porwal, Alok, Carranza, E. J. M., Hale, M.
Format:	Journal Article
Language:	English
Published:	Heidelberg Springer 01.03.2003 Springer Nature B.V
Subjects:	Areal geology. Maps Base metal Earth sciences Earth, ocean, space Exact sciences and technology Geologic maps, cartography Linear functions Mapping Metal geology Metallic and non-metallic deposits Mineral deposits Rajasthan India India models fuzzy sets exploration maps Asia interpretation fuzzy logic metallogenic provinces metals base metals potential deposits
ISSN:	1520-7439, 1573-8981
Online Access:	Get full text
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