煤炭工程 ›› 2017, Vol. 49 ›› Issue (2): 106-108.doi: 10.11799/ce201702033
• 研究探讨 • 上一篇 下一篇
郭西进
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摘要: 针对现有煤泥浮选加药量预测不准确的问题,提出了基于GA-BP神经网络作为煤泥浮选加药量的预测模型。首先通过MIV值评价法筛选出对浮选加药量影响较大的因素,进而建立了基于GA-BP神经网络的加药预测模型。用MIV值评价法完成了对网络结构的简化|用遗传算法优化神经网络的方法提高了神经网络模型预测加药量的精度。
关键词: BP神经网络, 浮选加药, MIV值评价法, 遗传算法
Abstract: In this paper, the prediction model of coal slime flotation dosage based on GA-BP neural network is present to dispose of the problems that the prediction is not accurate in the existing coal slime flotation dosage.Firstly, the influence factors are screened out through MIV value method,and then the prediction model based on GA-BP neural network of dosing is established.MIV value method is used to simplify the network structure ,and the method of genetic algorithm is employed to optimize the neural network to improve the accuracy of the neural network model to predict the dosage.
中图分类号:
TD679
郭西进,邵辉,王广胜,陈晓天. 基于GA-BP神经网络的浮选加药量预测[J]. 煤炭工程, 2017, 49(2): 106-108.
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