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Optimization decision-making method for slope stability of open pit coal mine waste dump
The invention discloses an opencast coal mine waste dump slope stability optimization decision-making method, which comprises the steps of obtaining a test data set based on factor information influencing the slope stability of an opencast coal mine waste dump; constructing a feedforward neural network model, and performing data feature extraction and nonlinear processing on the test data set; optimizing the weight and the threshold value of the feedforward neural network model by using a genetic algorithm; using a mean square error as a loss function to train and verify the feedforward neural network model to obtain a trained feedforward neural network model; and utilizing the trained feedforward neural network model to predict waste dump data to obtain a slope stability decision scheme. According to the method, the efficiency and accuracy of predicting the slope stability of the open pit coal mine waste dump are improved, the slope stability of the open pit coal mine waste dump can be analyzed more reliably, and powerful support is provided for disaster prevention and stability prediction of the open pit coal mine waste dump.
本发明公开了一种露天煤矿排土场边坡稳定性最优化决策方法，包括：基于影响露天矿场排土场边坡稳定性的因素信息，获取测试数据集；构建前馈神经网络模型，对测试数据集进行数据特征提取和非线性处理；利用遗传算法对前馈神经网络模型的权值和阈值进行优化；使用均方误差作为损失函数，对前馈神经网络模型进行训练和验证，得到训练后的前馈神经网络模型；利用训练后的前馈神经网络模型对排土场数据进行预测，得到边坡稳定性决策方案。本发明提高了预测露天煤矿排土场边坡稳定性的效率和准确性，能够更可靠地分析露天煤矿排土场边坡稳定性，为露天煤矿排土场的灾害预防和稳定预测提供有力支持。
Optimization decision-making method for slope stability of open pit coal mine waste dump
The invention discloses an opencast coal mine waste dump slope stability optimization decision-making method, which comprises the steps of obtaining a test data set based on factor information influencing the slope stability of an opencast coal mine waste dump; constructing a feedforward neural network model, and performing data feature extraction and nonlinear processing on the test data set; optimizing the weight and the threshold value of the feedforward neural network model by using a genetic algorithm; using a mean square error as a loss function to train and verify the feedforward neural network model to obtain a trained feedforward neural network model; and utilizing the trained feedforward neural network model to predict waste dump data to obtain a slope stability decision scheme. According to the method, the efficiency and accuracy of predicting the slope stability of the open pit coal mine waste dump are improved, the slope stability of the open pit coal mine waste dump can be analyzed more reliably, and powerful support is provided for disaster prevention and stability prediction of the open pit coal mine waste dump.
本发明公开了一种露天煤矿排土场边坡稳定性最优化决策方法，包括：基于影响露天矿场排土场边坡稳定性的因素信息，获取测试数据集；构建前馈神经网络模型，对测试数据集进行数据特征提取和非线性处理；利用遗传算法对前馈神经网络模型的权值和阈值进行优化；使用均方误差作为损失函数，对前馈神经网络模型进行训练和验证，得到训练后的前馈神经网络模型；利用训练后的前馈神经网络模型对排土场数据进行预测，得到边坡稳定性决策方案。本发明提高了预测露天煤矿排土场边坡稳定性的效率和准确性，能够更可靠地分析露天煤矿排土场边坡稳定性，为露天煤矿排土场的灾害预防和稳定预测提供有力支持。
Optimization decision-making method for slope stability of open pit coal mine waste dump
一种露天煤矿排土场边坡稳定性最优化决策方法
DUAN YUQIN (author) / ZU HUA (author) / WEN XIAODONG (author) / LI ZHEFENG (author) / HAN PENG (author) / LIU LIZHEN (author)
2025-01-03
Patent
Electronic Resource
Chinese
IPC:
G06F
ELECTRIC DIGITAL DATA PROCESSING
,
Elektrische digitale Datenverarbeitung
/
E02D
FOUNDATIONS
,
Gründungen
/
G06N
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
,
Rechnersysteme, basierend auf spezifischen Rechenmodellen
/
G06Q
Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke
,
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES
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