Application of a fuzzy inference system to mapping prospectivity for the Chahfiroozeh copper deposit, Kerman, Iran

Moghadam, Sanaz Alaei; Karimi, Mohammad; Mesgari, Mehran

doi:10.1080/14498596.2015.1004653

Cited by 6 publications

(4 citation statements)

References 28 publications

(37 reference statements)

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“…Number of study areas References Sudan 1 [39], [40], [41] Namibia 1 [42], [43], [44] Argentina 4 [45], [46], [47] , [48], [49], [50], [51], [52], [53], [54], [55], [56] Iran 4 [57], [58], [59], [60], [61], [62], [63], [64], [65] , [66], [67], [68], [69], [70] Pakistan 3 [71], [72], [73], [74], [75], [76] , [77], USA 5 [71], [78], [79], [80], [81], [82], [83] [84], [85], [86], [87] , [88], [89]…”

Section: Regionmentioning

confidence: 99%

From Pixels to Deposits: Porphyry Mineralization With Multispectral Convolutional Neural Networks

Zidan,

Desouky,

Gaber

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Mineral exploration is essential to ensure a sustainable supply of raw materials for modern living and the transition to green. It implies a series of expensive operations that aim to identify areas with natural mineral concentration in the crust of the Earth. The rapid advances in artificial intelligence and remote sensing techniques can help in significantly reducing the cost of these operations. Here, we produce a robust intelligent mineral exploration model that can fingerprint potential locations of porphyry deposits, which are the world's most important source of copper and molybdenum and major source of gold, silver, and tin. We present a deep learning pipeline for assessing multispectral imagery from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with the objective of identifying hydrothermal alterations. Our approach leverages a Convolutional Neural Network (ConvNet) to analyze the highresolution images, overcoming computational challenges through a patch-based strategy that involves an overlapping window for partitioning the images into fixed-size patches. Through the utilization of manually labeled patches for image classification and identification of hydrothermal alteration areas, our results demonstrate the remarkable ability of ConvNet to accurately detect hydrothermal alterations. The technique is adaptable for other ore deposit models and satellite imagery types, providing a revolution in satellite image interpretation and mineral exploration.

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Section: Regionmentioning

confidence: 99%

From Pixels to Deposits: Porphyry Mineralization With Multispectral Convolutional Neural Networks

Zidan,

Desouky,

Gaber

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…Xu et al (2011) apply a fuzzy relation model to analyze the amount of coal gas in mines; this model was applied to predict the spatial distribution of coal gas content in the air. In Moghadam et al (2015) a framework based on fuzzy relations and a fuzzy inference system is implemented to construct mineral potential maps.…”

Section: Related Workmentioning

confidence: 99%

A GIS-based framework using fuzzy relation equation system solutions in urban planning

Cardone

Martino

2022

J Ambient Intell Human Comput

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Several fuzzy decision models are proposed in literature to solve urban planning problems. In this research we present a novel GIS-based framework to solve decision problems in urban planning based on a System of Fuzzy Relation Equations in which the unknowns represent characteristics affecting observable facts constituting the input variables. Aim of this research is to partition the urban study area into subzones, each of which identifies a sub-area of the study area within which the set of analyzed characteristics are homogeneous. The study area is initially decomposed in atomic urban areas called microzones; for each microzone are calculated the greatest and lowest solutions of a System of Fuzzy Relation Equations by using the Universal solution Algorithm and are calculated and fuzzified the values of the output variables. Spatially adjoining microzones with same output variables are dissolved forming homogeneous urban areas with reference to the problem analyzed, called Urban Contexts. For each output variable a thematic map is constructed; in addition, a thematic map of its reliability is created. This framework is tested on a study area given by the district of Ponticelli in the municipality of Naples (Italy); comparison tests performed with respect to a previous GIS-based framework based on a System of Fuzzy Relation Equations show that our method provides a more detailed knowledge of the characteristics of the urban study area with reference to the problem dealt with.

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“…The membership function of each class is shown below in Figure 1. The figure presents an overview of the seven individual membership functions which are mathematically specified in Equations ( 4)- (10). Some researchers believe that the use of the Mamdani and Sugeno methods yields the same results [64,65].…”

Section: Variable Range Debt-to-equity Ratiomentioning

confidence: 99%

“…The results indicated that these sets of constraints lead to similar constraint categories with output fuzzy trained systems. Moghadam et al [10] used the FIS method to map the model. They found that a fuzzy inference system could be helpful in this type of research.…”

Section: Introductionmentioning

confidence: 99%

A Credit Rating Model in a Fuzzy Inference System Environment

et al. 2019

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One of the most important functions of an export credit agency (ECA) is to act as an intermediary between national governments and exporters. These organizations provide financing to reduce the political and commercial risks in international trade. The agents assess the buyers based on financial and non-financial indicators to determine whether it is advisable to grant them credit. Because many of these indicators are qualitative and inherently linguistically ambiguous, the agents must make decisions in uncertain environments. Therefore, to make the most accurate decision possible, they often utilize fuzzy inference systems. The purpose of this research was to design a credit rating model in an uncertain environment using the fuzzy inference system (FIS). In this research, we used suitable variables of agency ratings from previous studies and then screened them via the Delphi method. Finally, we created a credit rating model using these variables and FIS including related IF-THEN rules which can be applied in a practical setting.

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Application of a fuzzy inference system to mapping prospectivity for the Chahfiroozeh copper deposit, Kerman, Iran

Cited by 6 publications

References 28 publications

From Pixels to Deposits: Porphyry Mineralization With Multispectral Convolutional Neural Networks

From Pixels to Deposits: Porphyry Mineralization With Multispectral Convolutional Neural Networks

A GIS-based framework using fuzzy relation equation system solutions in urban planning

A Credit Rating Model in a Fuzzy Inference System Environment

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