INTELLECTUAL FORECASTING OF LANDSLIDES - Kairanbayeva, A.B.; Panyukova, D.V.; Nurpeissova, G.B.; Turekulova, K.A. (Academic Scientific Journal of Computer Science, 2020)
All over the world remote monitoring and satellite imaginary is taking part in urban and construction planning. Therefore, while biggest city of Republic of Kazakhstan is placed on a land with a risk of landslides, it is reasonable to use satellite technologies to assess the land surface deformation before construction started. The remote monitoring is providing results as an array of numeric data that can be converted into a surface map. However, besides real time monitoring of possible landslides, it is possible to forecast such deformation in dynamic. Such dynamical model is presented as an array of time series of parameters, which then can be converted into dynamically changed map. Analytical modeling can provide such forecasting with high accuracy but demand decent amount of data for every forecasting case. Intellectual methods of forecasting operate with lack of information and provide results with acceptable margin of error. Authors suggest designing intellectual models on periodic data from satellite images for landslides’ forecasting. Moreover, best-designed model can become a base for software package to provide such dynamic modeling of land’s deformation online for public and private use.