Machine learning for digital soil mapping: Applications, challenges and suggested solutions
The uptake of machine learning (ML) algorithms in digital soil mapping (DSM) is
transforming the way soil scientists produce their maps. Within the past two decades, soil …
transforming the way soil scientists produce their maps. Within the past two decades, soil …
Link prediction in complex networks using node centrality and light gradient boosting machine
Link prediction is amongst the most crucial tasks in network science and graph data
analytics. Given the snapshot of a network at a particular instance of time, the study of link …
analytics. Given the snapshot of a network at a particular instance of time, the study of link …
AgriSuit: A web-based GIS-MCDA framework for agricultural land suitability assessment
A web-based framework (AgriSuit) that integrates various global data from different sources
for multi-criteria based agricultural land suitability assessment based on the Google Earth …
for multi-criteria based agricultural land suitability assessment based on the Google Earth …
[HTML][HTML] A regression tree approach using mathematical programming
Regression analysis is a machine learning approach that aims to accurately predict the
value of continuous output variables from certain independent input variables, via automatic …
value of continuous output variables from certain independent input variables, via automatic …
A pattern recognition approach for detecting power islands using transient signals—Part I: Design and implementation
NWA Lidula, AD Rajapakse - IEEE Transactions on Power …, 2010 - ieeexplore.ieee.org
A novel, pattern-recognition-based approach for fast detection of power islands in a
distribution network is investigated. The proposed method utilizes transient signals …
distribution network is investigated. The proposed method utilizes transient signals …
Analysing the impact of soil spatial sampling on the performances of Digital Soil Mapping models and their evaluation: A numerical experiment on Quantile Random …
It has long been acknowledged that the soil spatial samplings used as inputs to DSM
models are strong drivers–and often limiting factors–of the performances of such models …
models are strong drivers–and often limiting factors–of the performances of such models …
Understanding relationships between conflicting human uses and coastal ecosystems status: a geospatial modeling approach
Human use of ecosystem resources and services is increasing worldwide, generating
pressures that alter ecosystem structure, functioning and provision of services. Unexpected …
pressures that alter ecosystem structure, functioning and provision of services. Unexpected …
Is image-based CAPTCHA secure against attacks based on machine learning? An experimental study
FH Alqahtani, FA Alsulaiman - Computers & Security, 2020 - Elsevier
The completely automated public Turing test to tell computers and humans apart
(CAPTCHA) is among the most common methods of authentication used by websites and …
(CAPTCHA) is among the most common methods of authentication used by websites and …
Understanding geometrical size effect on fatigue life of A588 steel using a machine learning approach
WK Yang, BL Hu, YW Luo, ZM Song… - International Journal of …, 2023 - Elsevier
In this paper, both experimental and machine learning results show that the fatigue life of
A588 steel specimens with different gauge lengths and widths varies more greatly compared …
A588 steel specimens with different gauge lengths and widths varies more greatly compared …
Analysis of the causes of wetland landscape patterns and hydrological connectivity changes in Momoge National Nature Reserve based on the Google Earth Engine …
G Cui, Y Liu, S Tong - Arabian Journal of Geosciences, 2021 - Springer
A wetland is a natural complex formed by the combined processes of land and water. Owing
to its rich biodiversity, high productivity, and unique ecological function, wetlands are …
to its rich biodiversity, high productivity, and unique ecological function, wetlands are …