Skoči na glavni sadržaj

Izvorni znanstveni članak

https://doi.org/10.17559/TV-20200429151307

Calculation Method of Probability Integration Method Parameters Based on MIV-GP-BP Model

Shenshen Chi ; 1) School of Earth and Environment, Anhui University of Science and Technology 2) School of Geomatics, Anhui University of Science and Technology 3) Key Laboratory of Aviation-aerospace-ground Cooperative Monitoring and Early Warning of Coal Mining-induced Disasters of Anhui Higher Education Institutes, Anhui University of Science and Technology 4) Coal Industry Engineering Research Center of Mining Area Environmental and Disaster Cooperative Monitoring, Anhui University of Science and Technology
Xuexiang Yu* ; School of Geomatics, Anhui University of Science and Technology, Huainan, 232001, China
Lei Wang ; School of Geomatics, Anhui University of Science and Technology, Huainan, 232001, China


Puni tekst: engleski pdf 523 Kb

str. 160-168

preuzimanja: 553

citiraj


Sažetak

In order to guarantee the precision of the parameters of the probability integral method (PIM), starting from optimizing input and improving algorithm an algorithm integrating the genetic algorithm (GA) and particle swarm optimization (PSO) was put forward to optimize the prediction model of BP neural network and the mean impact value algorithm (MIV) was applied to optimize the input of BP neural network. The mean impact value algorithm (MIV) was applied to optimize the input of BP neural network. The measured data of 50 working faces were chosen as the training and testing sets to build the MIV-GP-BP model. The results showed that among the five parameters, the RMSE was between 0.0058 and 1.1575, the MaxRE of q, tanβ, b and θ was less than 5.42%, and the MeaRE was less than 2.81%. The RMSE of s/H did not exceed 0.0058, the MaxRE was less than 9.66% and the MeaRE was less than 4.31% (the parameters themselves were small). The optimized neural network model had higher prediction accuracy and stability.

Ključne riječi

BP neural network; MIV algorithm; mining subsidence; optimization algorithm; PIM; underground mining

Hrčak ID:

251534

URI

https://hrcak.srce.hr/251534

Datum izdavanja:

5.2.2021.

Posjeta: 1.481 *