本文選題：因果關系 + 影響因素延遲�。� 參考：《信息與控制》2016年06期

【摘要】：在鋼鐵企業(yè)能源系統(tǒng)的低壓氮氣使用過程中,由于氮氣使用單元分散且在管網(wǎng)中的位置不同,對管網(wǎng)壓力的影響會出現(xiàn)短時間的延遲.鑒于此種情況,本文提出了一種基于影響因素輸入延遲的多核最小二乘支持向量機對管網(wǎng)壓力進行建模預測.該方法首先對低壓氮氣壓力影響因素的延遲時間進行確定,提出一種基于因果關系的影響因素延遲時間計算方法,同時根據(jù)不同的影響因素和對應的延遲時間分別構造訓練樣本,進而建立基于最小二乘支持向量機的預測模型.通過對某鋼鐵企業(yè)現(xiàn)場低壓氮氣管網(wǎng)壓力的兩種不同情況,即正常工況和超限工況分別進行建模仿真驗證,說明了本文提出的方法在壓力預測上具有較高的精度.
[Abstract]:In the process of low pressure nitrogen use in the energy system of iron and steel enterprises, the influence of nitrogen gas use units on the pressure of pipeline network will be delayed for a short time because of the dispersion of nitrogen gas using units and the different positions in the pipe network. In view of this situation, a multi-kernel least squares support vector machine (LS-SVM) based on the influence factor input delay is proposed to model and predict the pipe network pressure. In this method, the delay time of the influencing factors of low pressure nitrogen pressure is first determined, and a method of calculating the delay time of influencing factors based on causality is proposed. At the same time, the training samples are constructed according to different influencing factors and the corresponding delay time, and then the prediction model based on least squares support vector machine is established. By modeling and simulating two different situations of pressure of low pressure nitrogen pipe network in an iron and steel enterprise, that is, normal working condition and over-limit working condition, it is proved that the method proposed in this paper has high precision in pressure prediction.
【作者單位】： 大連理工大學控制科學與工程學院;
【基金】：國家自然科學基金資助項目(61304213,61473056)
【分類號】：TF083;TP181
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本文編號：1797910