Fuzzy Modeling of Surficial Uranium Prospectivity in British Columbia (Canada) with a Weighted Fuzzy Algebraic Sum Operator

Emmanuel John M. Carranza

doi:10.1007/s12583-021-1403-5

Volume 32 Issue 2

Apr 2021

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Journal of Earth Science > 2021 > 32(2): 293-309.

Emmanuel John M. Carranza. Fuzzy Modeling of Surficial Uranium Prospectivity in British Columbia (Canada) with a Weighted Fuzzy Algebraic Sum Operator. Journal of Earth Science, 2021, 32(2): 293-309. doi: 10.1007/s12583-021-1403-5

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Emmanuel John M. Carranza. Fuzzy Modeling of Surficial Uranium Prospectivity in British Columbia (Canada) with a Weighted Fuzzy Algebraic Sum Operator. Journal of Earth Science, 2021, 32(2): 293-309. doi: 10.1007/s12583-021-1403-5

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Fuzzy Modeling of Surficial Uranium Prospectivity in British Columbia (Canada) with a Weighted Fuzzy Algebraic Sum Operator

doi: 10.1007/s12583-021-1403-5

Emmanuel John M. Carranza^{,
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School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4041, South Africa

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Corresponding author: Emmanuel John M. Carranza, ejmcarranza@gmail.com
Received Date: 22 Nov 2020
Accepted Date: 22 Dec 2020
Publish Date: 01 Apr 2021

Abstract

Abstract

This paper demonstrates knowledge-guided fuzzy logic modeling of regional-scale surficial uranium (U) prospectivity in British Columbia (Canada). The deposits/occurrences of surficial U in this region vary from those in Western Australia and Namibia; thus, requiring innovative and carefully-thought techniques of spatial evidence generation and integration. As novelty, this papers introduces a new weighted fuzzy algebraic sum operator to combine certain spatial evidence layers. The analysis trialed several layers of spatial evidence based on conceptual mineral system model of surficial U in British Columbia (Canada) as well as tested various models of evidence integration. Non-linear weighted functions of (a) spatial closeness to U-enriched felsic igneous rocks was employed as U-source spatial evidence, (b) spatial closeness to paleochannels as fluid pathways spatial evidence, and (c) surface water U content as chemical trap spatial evidence. The best models of prospectivity created by integrating the layers of spatial evidence for U-source, pathways and traps predicted at least 85% of the known surficial U deposits/occurrences in > 10% of the study region with the highest prospectivity fuzzy scores. The results of analyses demonstrate that, employing the known deposits/occurrences of surficial U for scrutinizing the spatial evidence layers and the final models of prospectivity can pinpoint the most suitable critical processes and models of data integration to reduce bias in the analysis of mineral prospectivity.
- fuzzy logic,
- mineral systems,
- surficial uranium,
- fuzzy algebraic sum

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Fuzzy Modeling of Surficial Uranium Prospectivity in British Columbia (Canada) with a Weighted Fuzzy Algebraic Sum Operator

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Fuzzy Modeling of Surficial Uranium Prospectivity in British Columbia (Canada) with a Weighted Fuzzy Algebraic Sum Operator

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