Optimization of Process Control Parameters for Fully Mechanized Mining Face Based on ANN and GA.

ABSTRACT: In the traditional optimization mathod, the process control parameters for fully mechanized mining face are determined by experts or technicians based on their own experience, which is lack of scientific basis, and need long production adjustment cycle. It is cause large loss, and not conducive to improving mine production efficiency. In order to solve this problem, the study proposes a process control parameter optimization method based on a mixed strategy of artificial neural network and genetic algorithm and uses a cross-entropy cost function to optimize an artificial neural network, which improves the learning speed and fitting accuracy of the neural network. Using the historical production data of a fully mechanized coal mining face, taking the pulling speed of the shearer, hydraulic

SUBMITTER: Zhao H 

PROVIDER: S-EPMC8169252 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature