Neural Networks In Mining Sciences – General Overview And Some Representative Examples

Journal title

Archives of Mining Sciences




No 4

Publication authors

Divisions of PAS

Nauki o Ziemi


Archives of Mining Sciences (AMS) publish research results of wide interest in all fields of mining sciences which include: rock mechanics, mining engineering, mineral processing, geotechnical engineering and tunnelling, mining and engineering geology, minig geodesy and geophysics, ventilation systems, environmental protection in mining and economical aspects in mining.

The journal established by the Polish Academy of Sciences, has been regularly issued since 1956. It enable collaboration and exchange of ideas between researchers from different countries as well as provides forum for the publication of high quality papers.

Services indexing the journal: Astrophysics Data System (ADS), Baidu Scholar, BazTech, Celdes, Chemical Abstracts Service (CAS), Chemical Abstracts Service (CAS) – SciFinder, CNKI Scholar (China National Knowledge Infrastructure), CNPIEC, EBSCO - TOC Premier, EBSCO Discovery Service, EEVL, Genamics, JournalSeek, GeoRef, Google Scholar, Inspec, J-Gate, JournalTOCs, Naviga (Softweco), PKP, Primo Central (ExLibris), ProQuest (relevant databases), ReadCube, ResearchGate, Summon (Serials Solutions/ProQuest), TDOne (TDNet), TEMA Technik und Management, Thomson Reuters - Journal Citation Reports/Science Edition, Thomson Reuters - Science Citation Index Expanded, U.S. Geological Survey Library, Ulrich's Periodicals Directory/ulrichsweb WorldCat (OCLC).

IMPACT FACTOR 2017: 0.629, 5-year: 0,706

Score of the Ministry of Science and Higher Education = 20


Committee of Mining PAS


2015[2015.01.01 AD - 2015.12.31 AD]


ISSN 0860-7001


Silva (2015), Artificial neural networks to support petrographic classification of carbonate - siliciclastic rocks using well logs and textural information of vol, Journal Applied Geophysics, 118, ; Asoodeh (2015), The Estimation of Stoneley Wave Velocity from Conventional Well Log Data : Using an Integration of Artificial Neural Networks Part A Utilization , and Environmental Effects ) vol no, Energy Sources Recovery, 3, 309, ; Wonseok (2014), Development and application of the artificial neural network based technical screening guide system to select production methods in a coalbed methane reservoir - Exploration - and - Exploitation, Energy, 32, 791. ; Aliouane (2013), Fractal analysis based on the continuous wavelet transform and lithofacies classification from well - logs data using the self - organizing map neural network of Geosciences, Arabian Journal, 6, 1681, ; Morshedi (2014), The simulation of microbial enhanced oil recovery by using a two - layer perceptron neural network and Technology vol no, Petroleum Science, 22, 2700, ; Konate (2015), Capability of self - organizing map neural network in geophysical log data classification : Case study from the CCSD - MH of vol, Journal Applied Geophysics, 37, ; Ghiasi Freez (2012), The Application of Committee Machine with Intelligent Systems to the Prediction of Permeability from Petrographic Image Analysis and well logs Data : a case Study from the South pars gas Field South Iran and Technology, Petroleum Science, 30, 20. ; Olatunji (2013), Extreme Learning Machines Based Model for Predicting Permeability of Carbonate Reservoir of Digital Content Technology and its Applications, International Journal, 7, 450. ; Nooruddin (2014), Using soft computing techniques to predict corrected air permeability using Thomeer parameters air porosity and grain density Computers vol, Geosciences, 72. ; Wei Zheng (2014), Complex lithology automatic identification technology based on fuzzy clustering and neural networks th International Conference on Fuzzy Systems and Knowledge Discovery, IEEE, 227. ; Wei (2014), An effective detection method based on IPSO - WNN for acoustic telemetry signal of well logging while drilling International - Conference - on - Information - Electronics - and - Electrical - Engineering - ISEEE, Science, 49. ; Li Yang (2012), Application of factor neural network in multi - expert system for oil - gas reservoir protection of Theoretical and Applied Information Technology, Journal, 46, 303. ; Ghiasi (2015), Rigorous models to optimise stripping gas rate in natural gas dehydration units, Fuel, 140.