One method for probabilistic prediction of the material composition of deep crustal horizons using the geophysical data

被引：1
|
作者：
Lelyaev, P. A. [1 ]
机构：
[1] Russian Acad Sci, Schmidt Inst Phys Earth, Moscow 123995, Russia
来源：
IZVESTIYA-PHYSICS OF THE SOLID EARTH | 2011年 / 47卷 / 12期
关键词：
algorithm; Earth's crust; seismic velocities; density;
D O I：
10.1134/S1069351311080039
中图分类号：
P3 [地球物理学]; P59 [地球化学];
学科分类号：
0708 ; 070902 ;
摘要：
Prediction of the material composition of deep crustal horizons in the Earth from the geophysical data requires an algorithm to classify the rocks according to their petrophysical properties. In the present work, we propose a classification algorithm that is based on the membership function and describe the computer program, which is based on this algorithm and intended for visualization of the most typical crystalline rocks of the Voronezh massif.
引用
收藏
页码：1083 / 1085
页数：3
相关论文
共 50 条
  • [41] Probabilistic Flood Prediction in the Upper Huaihe Catchment Using TIGGE Data
    赵琳娜
    齐丹
    田付友
    吴昊
    狄靖月
    王志
    李爱华
    ActaMeteorologicaSinica, 2012, 26 (01) : 62 - 71
  • [42] Probabilistic flood prediction in the upper Huaihe catchment using TIGGE data
    Linna Zhao
    Dan Qi
    Fuyou Tian
    Hao Wu
    Jingyue Di
    Zhi Wang
    Aihua Li
    Acta Meteorologica Sinica, 2012, 26 : 62 - 71
  • [43] ProbFold: a probabilistic method for integration of probing data in RNA secondary structure prediction
    Sahoo, Sudhakar
    Switnicki, Michal P.
    Pedersen, Jakob Skou
    BIOINFORMATICS, 2016, 32 (17) : 2626 - 2635
  • [44] Martensite Start Temperature Prediction through a Deep Learning Strategy Using Both Microstructure Images and Composition Data
    Yang, Zenan
    Li, Yong
    Wei, Xiaolu
    Wang, Xu
    Wang, Chenchong
    MATERIALS, 2023, 16 (03)
  • [45] A new method for company failure prediction using probabilistic neural networks
    Yang, ZR
    8TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING, VOLS 1-3, PROCEEDING, 2001, : 841 - 846
  • [46] Traffic speed prediction using deep learning method
    Jia, Yuhan
    Wu, Jianping
    Du, Yiman
    2016 IEEE 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2016, : 1217 - 1222
  • [47] A probabilistic method for structural damage identification using uncertain data
    Zhou, J
    Feng, X
    Fan, YF
    STRUCTURAL HEALTH MONITORING AND INTELLIGENT INFRASTRUCTURE, VOLS 1 AND 2, 2003, : 487 - 492
  • [48] Container logistics in Mercosur: Choice of a transhipment port using the ordinal Copeland method, data envelopment analysis and probabilistic composition
    Caillaux, Marcio Arzua
    Sant'Anna, Annibal Parracho
    Meza, Lidia Angulo
    Baptista Soares de Mello, Joao Carlos Correia
    MARITIME ECONOMICS & LOGISTICS, 2011, 13 (04) : 355 - 370
  • [49] Container logistics in Mercosur: Choice of a transhipment port using the ordinal Copeland method, data envelopment analysis and probabilistic composition
    Márcio Arzua Caillaux
    Annibal Parracho Sant'Anna
    Lidia Angulo Meza
    João Carlos Correia Baptista Soares de Mello
    Maritime Economics & Logistics, 2011, 13 : 355 - 370
  • [50] Material Cost Prediction for Jewelry Production Using Deep Learning Technique
    Phitthayanon, Chanida
    Rungreunganun, Vichai
    ENGINEERING JOURNAL-THAILAND, 2019, 23 (06): : 145 - 160
12345