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Fuzzy logic fusion of W-Mo exploration data from Seobyeog-ri, Korea
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/bf00893171openalex-snapshot
Interpolation by regularized spline with tension: I. Theory and implementation
inferredcites →https://doi.org/10.1007/bf00893172openalex-snapshot
Interpolation by regularized spline with tension: II. Application to terrain modeling and surface geometry analysis
inferredcites →https://doi.org/10.1007/bf02261716openalex-snapshot
Uncertainty management in integration of exploration data using the belief function
inferredcites →https://doi.org/10.1016/0165-0114(78)90029-5openalex-snapshot
Fuzzy sets as a basis for a theory of possibility
inferredcites →https://doi.org/10.1016/0165-0114(80)90062-7openalex-snapshot
Latent connectives in human decision making
inferredcites →https://doi.org/10.1016/s0165-0114(99)80004-9openalex-snapshot
Fuzzy sets as a basis for a theory of possibility
inferredcites →https://doi.org/10.1080/07038992.1993.10855151openalex-snapshot
On Mathematical Representation and Integration of Multiple Spatial Geoscience Data Sets
inferredcites →https://doi.org/10.1109/tgrs.1990.572988openalex-snapshot
Integration Of Geophysical And Geological Data Using Evidential Belief Function
inferredcites →https://doi.org/10.2113/gsecongeo.42.5.465openalex-snapshot
The Sangdong tungsten deposit, southern Korea
inferredcites →https://doi.org/10.2113/gsecongeo.58.8.1285openalex-snapshot
Geology and origin of Sangdong tungsten mine, Republic of Korea
inferredcites →https://doi.org/10.2113/gsecongeo.73.4.547openalex-snapshot
Age of the Sangdong tungsten deposit, Republic of Korea, and its bearing on the metallogeny of the southern Korean Peninsula
inferredcites →https://doi.org/10.4095/128059openalex-snapshot
Weights of evidence modelling: a new approach to mapping mineral potential
inferredcites →https://doi.org/10.5860/choice.32-6239openalex-snapshot
Geographic information systems for geoscientists: modelling with GIS
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-95083-4_10openalex-snapshot
GIS-Based Landslide Susceptibility Mapping of the Darjiling Himalaya, India Using Frequency Ratio (FR) and Fuzzy Logic (FL) Models
inferred← citeshttps://doi.org/10.1007/bf02912690openalex-snapshot
Multi-sensor data fusion for supervised land-cover classification using Bayesian and geostatistical techniques
inferred← citeshttps://doi.org/10.1007/s11053-017-9348-1openalex-snapshot
Natural Resources Research Publications on Geochemical Anomaly and Mineral Potential Mapping, and Introduction to the Special Issue of Papers in These Fields
inferred← citeshttps://doi.org/10.1007/s12040-015-0536-2openalex-snapshot
Landslide susceptibility zonation in part of Tehri reservoir region using frequency ratio, fuzzy logic and GIS
inferred← citeshttps://doi.org/10.1007/s12518-013-0111-yopenalex-snapshot
Predictive mapping for porphyry copper mineralization: a comparison of knowledge-driven and data-driven fuzzy models in Siahrud area, Azarbaijan province, NW Iran
inferred← citeshttps://doi.org/10.1007/s12665-019-8285-1openalex-snapshot
A comparison of frequency ratio and fuzzy logic models for flood susceptibility assessment of the lower Kosi River Basin in India
inferred← citeshttps://doi.org/10.1109/icsdm.2011.5969034openalex-snapshot
Mineral prospectivity mapping integrating multi-source geology spatial data sets and logistic regression modelling
inferred← citeshttps://doi.org/10.1186/s40677-014-0009-yopenalex-snapshot
Landslide hazard zonation mapping using frequency ratio and fuzzy logic approach, a case study of Lachung Valley, Sikkim
inferred← citeshttps://doi.org/10.22060/ajce.2018.14235.5465openalex-snapshot
A Combined Model for Landslide Susceptibility, Hazard and Risk Assessment
inferred← citeshttps://doi.org/10.3390/min13101302openalex-snapshot
Prediction of Au-Polymetallic Deposits Based on Spatial Multi-Layer Information Fusion by Random Forest Model in the Central Kunlun Area of Xinjiang, China
inferred← citeshttps://doi.org/10.3390/rs17152689openalex-snapshot
Current Progress in and Future Visions of Key Technologies of UAV-Borne Multi-Modal Geophysical Exploration for Mineral Exploration: A Scoping Review
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