当代化工
噹代化工
당대화공
CONTEMPORARY CHEMICAL INDUSTRY
2015年
4期
789-791
,共3页
王飞%阿斯汉%王卫强%柴多
王飛%阿斯漢%王衛彊%柴多
왕비%아사한%왕위강%시다
天然气%水合物%生成条件%最小二乘支持向量机
天然氣%水閤物%生成條件%最小二乘支持嚮量機
천연기%수합물%생성조건%최소이승지지향량궤
Natural gas%Hydrate%Formation conditions%Least squares support vector machine
在天然气管线内生成的水合物会严重影响天然气的开采、运输,因而天然气水合物的预测方法和防治措施备受重视。针对天然气水合物生成条件,考虑天然气组分对水合物生成的影响,为简化计算、提高预测精度,引入一种能够很好解决复杂物理问题的最小二乘支持向量机(LS-SVM),并且通过Matlab语言编程,建立了一种包含CH4浓度、CO2浓度、H2S浓度以及水合物生成温度为输入,水合物生成压强为输出的天然气水合物生成条件预测模型,同时将实验数据作为最小二乘支持向量机训练数据并进行预测分析。结果表明,该预测模型不仅拥有较高的预测精度,而且方法简单、可行,为天然气水合物生成条件预测提供了一种新的解决方法。
在天然氣管線內生成的水閤物會嚴重影響天然氣的開採、運輸,因而天然氣水閤物的預測方法和防治措施備受重視。針對天然氣水閤物生成條件,攷慮天然氣組分對水閤物生成的影響,為簡化計算、提高預測精度,引入一種能夠很好解決複雜物理問題的最小二乘支持嚮量機(LS-SVM),併且通過Matlab語言編程,建立瞭一種包含CH4濃度、CO2濃度、H2S濃度以及水閤物生成溫度為輸入,水閤物生成壓彊為輸齣的天然氣水閤物生成條件預測模型,同時將實驗數據作為最小二乘支持嚮量機訓練數據併進行預測分析。結果錶明,該預測模型不僅擁有較高的預測精度,而且方法簡單、可行,為天然氣水閤物生成條件預測提供瞭一種新的解決方法。
재천연기관선내생성적수합물회엄중영향천연기적개채、운수,인이천연기수합물적예측방법화방치조시비수중시。침대천연기수합물생성조건,고필천연기조분대수합물생성적영향,위간화계산、제고예측정도,인입일충능구흔호해결복잡물리문제적최소이승지지향량궤(LS-SVM),병차통과Matlab어언편정,건립료일충포함CH4농도、CO2농도、H2S농도이급수합물생성온도위수입,수합물생성압강위수출적천연기수합물생성조건예측모형,동시장실험수거작위최소이승지지향량궤훈련수거병진행예측분석。결과표명,해예측모형불부옹유교고적예측정도,이차방법간단、가행,위천연기수합물생성조건예측제공료일충신적해결방법。
The hydrate generated in the natural gas pipeline will seriously affect the natural gas production, transportation, and the prediction methods and control measures of natural gas hydrate (NGH) have attracted great attention. For natural gas hydrate formation conditions, considering the influence of the components on the gas hydrate formation, in order to simplify the calculation and improve the prediction accuracy, through introducing least squares support vector machines (LS - SVM) and using Matlab language programming, a prediction model of natural gas hydrate formation conditions was established with the concentrations of CH4 , H2S , CO2 and hydrate formation temperature as the input, the pressure of hydrate formation as the output. At the same time, the experimental data were used as Least Squares Support Vector Machine training data to carry out the forecast analysis. The results show that the forecasting model has higher prediction accuracy, and the method is simple and feasible, can provide a new solution for prediction of natural gas hydrate formation conditions.