FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387643934> ?p ?o ?g. }

• W4387643934 endingPage "107326" @default.
• W4387643934 startingPage "107326" @default.
• W4387643934 abstract "When conducting Mineral Potential Mapping (MPM) using multiple sources of data such as geology, geochemistry, and geophysics, it often encounters the challenges of complex and diverse data distributions within these datasets. Enhancing the capability to extract nonlinear data features and further uncover metallogenic information is a crucial research objective. This study utilizes the C-A multifractal approach to extract anomalous information related to metallogenic elements, employs compositional data analysis methods for quantitatively extracting geochemical associations of mineralization, and utilizes GIS spatial analysis techniques to quantitatively extract predictive indicators from various data sources, including geology, geophysics, and remote sensing, to construct an MPM prediction dataset. Building upon the foundation of AutoEncoder (AE), this study introduces a discriminator and employs the AEGAN (Auto Encoder Generative Adversarial Network) algorithm, which combines AutoEncoder and Generative Adversarial Network (GAN), for metallogenic prospectivity prediction in the Lhasa region. Compared to AE algorithms, AEGAN combines the strengths of AE and GAN, significantly improving the model's ability to reconstruct input data through the interaction between the generator and discriminator. Additionally, this study designs comparative experiments with AE, and the results demonstrate that the AEGAN model can more accurately identify the correlation between high anomaly areas and polymetallic deposits, providing a more precise delineation of anomalous extents. The Area Under the Receiver Operating Characteristic Curve (AUC) further validates the superior performance of the AEGAN model. These findings indicate that the AEGAN model exhibits outstanding capabilities in learning the internal connections and features among multiple data sources, holding significant potential for practical applications in mineral exploration." @default.
• W4387643934 created "2023-10-15" @default.
• W4387643934 creator A5015773594 @default.
• W4387643934 creator A5022598327 @default.
• W4387643934 creator A5029484872 @default.
• W4387643934 creator A5045106460 @default.
• W4387643934 creator A5051273870 @default.
• W4387643934 creator A5088888717 @default.
• W4387643934 date "2023-10-01" @default.
• W4387643934 modified "2023-10-15" @default.
• W4387643934 title "Auto encoder generative adversarial networks - based mineral prospectivity mapping in Lhasa area, Tibet" @default.
• W4387643934 cites W1969818811 @default.
• W4387643934 cites W1973237440 @default.
• W4387643934 cites W2004780129 @default.
• W4387643934 cites W2005719312 @default.
• W4387643934 cites W2010457088 @default.
• W4387643934 cites W2018366608 @default.
• W4387643934 cites W2022970735 @default.
• W4387643934 cites W2025457721 @default.
• W4387643934 cites W2026992098 @default.
• W4387643934 cites W2040383206 @default.
• W4387643934 cites W2040904643 @default.
• W4387643934 cites W2047361407 @default.
• W4387643934 cites W2058274266 @default.
• W4387643934 cites W2063350328 @default.
• W4387643934 cites W2078112764 @default.
• W4387643934 cites W2098397292 @default.
• W4387643934 cites W2100495367 @default.
• W4387643934 cites W2115518283 @default.
• W4387643934 cites W2153796345 @default.
• W4387643934 cites W2159469384 @default.
• W4387643934 cites W2201593588 @default.
• W4387643934 cites W2267247365 @default.
• W4387643934 cites W2461102141 @default.
• W4387643934 cites W2564974494 @default.
• W4387643934 cites W2609739009 @default.
• W4387643934 cites W2615492166 @default.
• W4387643934 cites W2620372065 @default.
• W4387643934 cites W2767155774 @default.
• W4387643934 cites W2810936097 @default.
• W4387643934 cites W2896335697 @default.
• W4387643934 cites W2899056763 @default.
• W4387643934 cites W2945210856 @default.
• W4387643934 cites W2959587919 @default.
• W4387643934 cites W3016126888 @default.
• W4387643934 cites W3087687059 @default.
• W4387643934 cites W3096831136 @default.
• W4387643934 cites W3127268485 @default.
• W4387643934 cites W3171819295 @default.
• W4387643934 cites W3175535587 @default.
• W4387643934 cites W3192485199 @default.
• W4387643934 cites W3210475939 @default.
• W4387643934 doi "https://doi.org/10.1016/j.gexplo.2023.107326" @default.
• W4387643934 hasPublicationYear "2023" @default.
• W4387643934 type Work @default.
• W4387643934 citedByCount "0" @default.
• W4387643934 crossrefType "journal-article" @default.
• W4387643934 hasAuthorship W4387643934A5015773594 @default.
• W4387643934 hasAuthorship W4387643934A5022598327 @default.
• W4387643934 hasAuthorship W4387643934A5029484872 @default.
• W4387643934 hasAuthorship W4387643934A5045106460 @default.
• W4387643934 hasAuthorship W4387643934A5051273870 @default.
• W4387643934 hasAuthorship W4387643934A5088888717 @default.
• W4387643934 hasConcept C101738243 @default.
• W4387643934 hasConcept C108583219 @default.
• W4387643934 hasConcept C109007969 @default.
• W4387643934 hasConcept C124101348 @default.
• W4387643934 hasConcept C127313418 @default.
• W4387643934 hasConcept C151730666 @default.
• W4387643934 hasConcept C153180895 @default.
• W4387643934 hasConcept C154945302 @default.
• W4387643934 hasConcept C2779803651 @default.
• W4387643934 hasConcept C2988773926 @default.
• W4387643934 hasConcept C39890363 @default.
• W4387643934 hasConcept C41008148 @default.
• W4387643934 hasConcept C55358776 @default.
• W4387643934 hasConcept C739882 @default.
• W4387643934 hasConcept C76155785 @default.
• W4387643934 hasConcept C94915269 @default.
• W4387643934 hasConceptScore W4387643934C101738243 @default.
• W4387643934 hasConceptScore W4387643934C108583219 @default.
• W4387643934 hasConceptScore W4387643934C109007969 @default.
• W4387643934 hasConceptScore W4387643934C124101348 @default.
• W4387643934 hasConceptScore W4387643934C127313418 @default.
• W4387643934 hasConceptScore W4387643934C151730666 @default.
• W4387643934 hasConceptScore W4387643934C153180895 @default.
• W4387643934 hasConceptScore W4387643934C154945302 @default.
• W4387643934 hasConceptScore W4387643934C2779803651 @default.
• W4387643934 hasConceptScore W4387643934C2988773926 @default.
• W4387643934 hasConceptScore W4387643934C39890363 @default.
• W4387643934 hasConceptScore W4387643934C41008148 @default.
• W4387643934 hasConceptScore W4387643934C55358776 @default.
• W4387643934 hasConceptScore W4387643934C739882 @default.
• W4387643934 hasConceptScore W4387643934C76155785 @default.
• W4387643934 hasConceptScore W4387643934C94915269 @default.
• W4387643934 hasLocation W43876439341 @default.
• W4387643934 hasOpenAccess W4387643934 @default.
• W4387643934 hasPrimaryLocation W43876439341 @default.

• next