Experience the forecast of engineering geological properties subsiding horizons for designing of neural network method

  • T. P. Mokritskaya Dnipropetrovsk National University Oles Gonchar,
  • D. O. Kalinina Dnipropetrovsk National University Oles Gonchar,


The object of study: Geological environment that is within the influence of the designed structures located on housing estate Topol-3,  in the Dnepropetrovsk city.  Objective: Justification optimal method forecast of engineering-geological processes     on the results of the application of neural network technology. Method of research: quantitative and qualitative analysis       of the conditions and factors for the development of engineering-geological processes in the zone of influence of facilities. Mathematical modeling, statistics, correlation and regression analyzes of neural network technology. For the first time in Ukraine had applied neural network technology to forecast changes in soil properties in the zone of influence of facilities    that provide new opportunities for building design tasks. It was found that the areas of research in the geological structure of the array participate aeolian-diluvial quaternary sediments. In the geological section, explore to a depth of 26 m, the array    is allocated 6 geotechnical elements (GE), within which the thickness is statistically homogeneous in their properties. From  the analysis of the conditions and factors of development of engineering-geological processes it is known that it may develop by settling and subsidence. Statistical homogeneity of the sample data on the properties of the soil allows you to combine  data. In the future, changes in the properties of the simulation based on the analysis of this set. It was obtained forecast  values relative subsidence, strength, modulus of deformation in natural and humid condition on the basis of the application  of inductive methods of research. Quantitative analysis of the results indicates a significant difference between the predicted values of indicators obtained by the regulatory procedure, it points to the possible negative effects of the regulatory processes of forecasting techniques. In the future, we recommend the use of neural network technology to forecasting properties of soils in the area with affected structures.Key words: Neural network, Physical and mechanical properties of soils, geological forecasting, stochastic simulation, calculation of rainfall, the calculation of drawdown

Author Biographies

T. P. Mokritskaya, Dnipropetrovsk National University Oles Gonchar,
Dnipropetrovsk National University Oles Gonchar,prof., Dr.  Geol. Sciences
D. O. Kalinina, Dnipropetrovsk National University Oles Gonchar,
Dnipropetrovsk National University Oles Gonchar, student


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How to Cite
Mokritskaya, T., & Kalinina, D. (2016). Experience the forecast of engineering geological properties subsiding horizons for designing of neural network method. Journal of Geology, Geography and Geoecology, 24(1), 102-106. https://doi.org/https://doi.org/10.15421/111615