Orogenic gold prospectivity mapping using machine learning

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Dust source mapping using satellite imagery and machine learning models

Predicting dust sources area and determining the affecting factors is necessary in order to prioritize management and practice deal with desertification due to wind erosion in arid areas. Therefore, this study aimed to evaluate the application of three machine learning models (including generalized linear model, artificial neural network, random forest) to predict the vulnerability of dust cent...

متن کامل

GIS Modelling of Gold Prospectivity in New Zealand

Gold production in New Zealand has been significant since the mid 1800s, totalling 900 t (29 Moz) to 2005. In addition, there is potential for a further 1230 t (39.5 Moz) of gold in known and undiscovered deposits. Most of the gold has originated from epithermal and mesothermal (orogenic) hydrothermal systems. Epithermal gold occurs in the Northland, Coromandel and Taupo volcanic zones in quart...

متن کامل

Teamwork: Improved eQTL Mapping Using Combinations of Machine Learning Methods

Expression quantitative trait loci (eQTL) mapping is a widely used technique to uncover regulatory relationships between genes. A range of methodologies have been developed to map links between expression traits and genotypes. The DREAM (Dialogue on Reverse Engineering Assessments and Methods) initiative is a community project to objectively assess the relative performance of different computat...

متن کامل

Adaptive parallelism mapping in dynamic environments using machine learning

Modern day hardware platforms are parallel and diverse, ranging from mobiles to data centers. Mainstream parallel applications execute in the same system competing for resources. This resource contention may lead to drastic degradation in a program’s performance. In addition, the execution environment composed of workloads and hardware resources, is dynamic and unpredictable. Efficient matching...

متن کامل

Automatic CRP Mapping and Rectification using Nonparametric Machine Learning Approaches

This paper studies an uneven 2-class classification problem of satellite imagery, i.e., the mapping of United States Department of Agriculture (USDA)’s Conservation Reserve Program (CRP) tracts. CRP is a nationwide program that encourages farmers to plant long-term resource conserving covers to improve soil, water and wildlife resources. With the recent program development, it is imperative to ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: ASEG Extended Abstracts

سال: 2019

ISSN: 2202-0586

DOI: 10.1080/22020586.2019.12073020