Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Lingqing Yao"'
Publikováno v:
Mathematical Geosciences. 54:1097-1119
A new non-stationary, high-order sequential simulation method is presented herein, aiming to accommodate complex curvilinear patterns when modelling non-Gaussian, spatially distributed and variant attributes of natural phenomena. The proposed approac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aec57209dddfa1244c01b28a0e9deddc
https://doi.org/10.1007/s11004-022-10004-2
https://doi.org/10.1007/s11004-022-10004-2
Publikováno v:
Mathematical Geosciences
A training image free, high-order sequential simulation method is proposed herein, which is based on the efficient inference of high-order spatial statistics from the available sample data. A statistical learning framework in kernel space is adopted
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9ab80d01d54b1307f5f565c1b03c9a4
https://doi.org/10.1007/s11004-021-09923-3
https://doi.org/10.1007/s11004-021-09923-3
Autor:
Roussos Dimitrakopoulos, Lingqing Yao
Publikováno v:
Encyclopedia of Mathematical Geosciences ISBN: 9783030260507
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4da066833cf73c61c734a9166d151e3a
https://doi.org/10.1007/978-3-030-26050-7_16-1
https://doi.org/10.1007/978-3-030-26050-7_16-1
Publikováno v:
Mathematical Geosciences
The present work proposes a new high-order simulation framework based on statistical learning. The training data consist of the sample data together with a training image, and the learning target is the underlying random field model of spatial attrib
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb06b43e91f909e58218739ca68c2f07
https://doi.org/10.1007/s11004-019-09843-3
https://doi.org/10.1007/s11004-019-09843-3
Publikováno v:
In Journal of China University of Geosciences 2008 19(4):410-415
Publikováno v:
Computers & Geosciences. 149:104702
This paper presents a learning-based stochastic simulation method that incorporates high-order spatial statistics at multiple scales from sources with different resolutions. Regarding the simulation of a certain spatial attribute, the high-order spat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::23a886215d5415f2b499535920bd57ca
https://doi.org/10.1016/j.cageo.2021.104702
https://doi.org/10.1016/j.cageo.2021.104702
Publikováno v:
Acta Geologica Sinica - English Edition. 90:2066-2079
The Wurinitu Mo deposit is one of the newly found molybdenum deposits in the southwestern part of the late Paleozoic–Mesozoic Erenhot–Dong-Ujimqin metallogenic belt (S-EDMB), Inner Mongolia, China. In the present study, the mineralization age of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20f7721d7daf1c06e75b98e124e30a5e
https://doi.org/10.1111/1755-6724.13022
https://doi.org/10.1111/1755-6724.13022
Publikováno v:
Mathematical Geosciences
Multiple-point simulations have been introduced over the past decade to overcome the limitations of second-order stochastic simulations in dealing with geologic complexity, curvilinear patterns, and non-Gaussianity. However, a limitation is that they
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86f35322e0a39c68374b9fcead4e4107
https://pubmed.ncbi.nlm.nih.gov/30931019
https://pubmed.ncbi.nlm.nih.gov/30931019
Publikováno v:
Geochemistry: Exploration, Environment, Analysis. 14:265-276
Spatial distribution of geochemical elements at hand-specimen and outcrop scale provides significant evidence for the processes of formation and alteration of rocks. Portable X-ray fluorescence (pXRF) analyses is a non-destructive and cost-effective
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba0883850887108054aec41aa88d235b
https://doi.org/10.1144/geochem2012-173
https://doi.org/10.1144/geochem2012-173
Publikováno v:
International Journal of Applied Earth Observation and Geoinformation. 11:394-402
Geological point processes can be used to model point patterns occurring frequently in a wide variety of geoscience fields, including the study of mineral deposits, oil producing wells, earthquakes, and landslides. Characterization of the spatial dis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6d2fc17d456c76f61d8a7bb99e492201
https://doi.org/10.1016/j.jag.2009.07.001
https://doi.org/10.1016/j.jag.2009.07.001