Application of fuzzy logic and fuzzy AHP to mineral prospectivity mapping of porphyry and hydrothermal vein copper deposits in the Dananhu-Tousuquan island arc, Xinjiang, NW China

Zhang, Nannan; Zhou, Kefa; Du, Xishihui

doi:10.1016/j.jafrearsci.2016.12.011

Cited by 68 publications

(28 citation statements)

References 37 publications

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“…Fuzzy modelling allows flexible standardization and aggregation by partial membership. Numerous studies attempted to use fuzzy modelling in development of water quality index and water quality assessment (Dahiya et al 2007;Icaga 2007;S¸en 2009;Mofarrah & Husain 2011;Sahu et al 2011;Gharibi et al 2012;Liu & Zou 2012;Scannapieco et al 2012;Kord & Asghari Moghaddam 2014) or in the other proposes that are near to aim of our study (Chen & Paydar 2012;Lewis et al 2014;Akumu et al 2015;Caniani et al 2016;Araya-Muñoz et al 2017;Hellwig et al 2017;Zhang et al 2017). All of these researches are emphasized on the very high accuracy of the results due to use of the fuzzy logic method.…”

Section: Introductionmentioning

confidence: 87%

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Qualitative zoning of groundwater to assessment suitable drinking water using fuzzy logic spatial modelling via GIS

Tafreshi

Keshavarzi

2018

Water & Environment J

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Due to shortage of surface water, resources of ground water in Iran (like many other countries with dry and semi‐dry weather) have turned into the most important and reliable source for water supply. Thus, it is necessary to consider the quality of this resource for drinking purposes. The aim of this study was to assessment suitable drinking water based on a fuzzy approach in Asalem region, Iran. For reduce the uncertainty, fuzzy logic spatial modelling via GIS was applied. To receive these aims, four stages were performed. In stage 1, we calculate the values of eighteen conventional and effective factors used for drinking water quality classification upon analysing the statistical quality data regarding various ions existing in 15 sample wells dug in 2015. In stage 2, interpolate these factors by kriging method via ArcGIS software. In stage 3, parameter standardization with fuzzy membership function were done. And in stage 4, for Aggregation factors, several fuzzy overlay operations were used. Finally, to identify the best operation, the ‘Optimum Index Factor’ was used. Results showed that the ‘GAMMA 0.9’ with highest OIF in most of the factors, is the best overly operation in our study area. According to classified the best operation map, 1.42% of understudied regions are classified in very poor class, 12.48% is grouped in poor class, 78.55% is grouped in fair class, 7.53% is classified in good group and 0.01% is classified as excellent group. In this regard only central parts of the study area have ‘fair’ to ‘good’ and ‘excellent’ groundwater quality for drinking water and in other parts, the quality is within ‘very poor’ and ‘poor’ to ‘fair’.

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Section: Introductionmentioning

confidence: 87%

“…; Zhang et al . ). All of these researches are emphasized on the very high accuracy of the results due to use of the fuzzy logic method.…”

Section: Introductionmentioning

confidence: 97%

Qualitative zoning of groundwater to assessment suitable drinking water using fuzzy logic spatial modelling via GIS

Tafreshi

Keshavarzi

2018

Water & Environment J

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“…These components were integrated using a knowledge-driven approach based on fuzzy logic. The components were weighted from 1 to 10, using a subjective judgement based on the metallogenic models presented for hydrothermal mineralization and expert knowledge [79][80][81]. The more favorable the alteration type, the higher weight it took.…”

Section: Integration Of Hydrothermal Alteration Thematic Layers Usingmentioning

confidence: 99%

Integration of Selective Dimensionality Reduction Techniques for Mineral Exploration Using ASTER Satellite Data

et al. 2020

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There are a significant number of image processing methods that have been developed during the past decades for detecting anomalous areas, such as hydrothermal alteration zones, using satellite images. Among these methods, dimensionality reduction or transformation techniques are known to be a robust type of methods, which are helpful, as they reduce the extent of a study area at the initial stage of mineral exploration. Principal component analysis (PCA), independent component analysis (ICA), and minimum noise fraction (MNF) are the dimensionality reduction techniques known as multivariate statistical methods that convert a set of observed and correlated input variables into uncorrelated or independent components. In this study, these techniques were comprehensively compared and integrated, to show how they could be jointly applied in remote sensing data analysis for mapping hydrothermal alteration zones associated with epithermal Cu–Au deposits in the Toroud-Chahshirin range, Central Iran. These techniques were applied on specific subsets of the advanced spaceborne thermal emission and reflection radiometer (ASTER) spectral bands for mapping gossans and hydrothermal alteration zones, such as argillic, propylitic, and phyllic zones. The fuzzy logic model was used for integrating the most rational thematic layers derived from the transformation techniques, which led to an efficient remote sensing evidential layer for mineral prospectivity mapping. The results showed that ICA was a more robust technique for generating hydrothermal alteration thematic layers, compared to the other dimensionality reduction techniques. The capabilities of this technique in separating source signals from noise led to improved enhancement of geological features, such as specific alteration zones. In this investigation, several previously unmapped prospective zones were detected using the integrated hydrothermal alteration map and most of the known hydrothermal mineral occurrences showed a high prospectivity value. Fieldwork and laboratory analysis were conducted to validate the results and to verify new prospective zones in the study area, which indicated a good consistency with the remote sensing output. This study demonstrated that the integration of remote sensing-based alteration thematic layers derived from the transformation techniques is a reliable and low-cost approach for mineral prospectivity mapping in metallogenic provinces, at the reconnaissance stage of mineral exploration.

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“…While most of the available spatial datasets are limited to surface expressions of the mineral systems, surface topography, and geological features the combination of these datasets with expert knowledge and spatial analysis methods can provide insights into the ore-forming processes. Mineral Prospectivity Mapping (MPM) provides a structured quantitative methodology to integrate these multiple spatial datasets to analyse the distribution of mineral deposits and model their spatial association providing insights into the controls on ore deposition e.g., [1,[19][20][21][22][23][24]. MPM can utilise either a data-and knowledge-driven approach or some combination of both [25].…”

Section: Introductionmentioning

confidence: 99%

Prospectivity Mapping for Epithermal Deposits of Western Milos Using a Fuzzy Multi Criteria Evaluation Approach Parameterized by Airborne Hyperspectral Remote Sensing Data

et al. 2019

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A Mineral prospectivity mapping (MPM) approach using a GIS-based weighted linear combination implementation of a Multi-Criteria Evaluation approach utilising a fuzzy Analytical Hierarchy Process to elucidate expert knowledge has been implemented to analyse the spatial distribution of epithermal deposits on the Island of Milos, Greece and model their association with exploration evidence data with the aim of providing insights into the controls on ore deposition. An integrated field and Digital Airborne Imaging Spectrometer (DAIS) hyperspectral and thermal multispectral airborne remote sensing dataset supported by field mapping and laboratory analyses, has been utilised to resolve hydrothermal alteration and parameterise the MPM. This study has highlighted the intimate spatial relationship between topographic highs and locations with high grade silicified alteration at a number of locations. The ability of high spatial resolution multispectral Thermal InfraRed (TIR) remote sensing imagery, integrated with topographic data, to resolve these silicified topographic highs provides an additional tool in the exploration of epithermal deposits. The spatial relationships between silicified lithocaps, high-grade altered rocks, faulting and topographic highs were utilised in the development of the MPM model. A close association between the modelled results and the hydrothermal alteration mapped in the field supports the accuracy of this MPM approach.

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Application of fuzzy logic and fuzzy AHP to mineral prospectivity mapping of porphyry and hydrothermal vein copper deposits in the Dananhu-Tousuquan island arc, Xinjiang, NW China

Cited by 68 publications

References 37 publications

Qualitative zoning of groundwater to assessment suitable drinking water using fuzzy logic spatial modelling via GIS

Qualitative zoning of groundwater to assessment suitable drinking water using fuzzy logic spatial modelling via GIS

Integration of Selective Dimensionality Reduction Techniques for Mineral Exploration Using ASTER Satellite Data

Prospectivity Mapping for Epithermal Deposits of Western Milos Using a Fuzzy Multi Criteria Evaluation Approach Parameterized by Airborne Hyperspectral Remote Sensing Data

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