Baosteel＇ s Slag Short Flow（BSSF） is an innovative process for steelmaking slag treatment that was developed by Baosteel. The process principles, flow-chart, parameters and component systems of the BSSF for steelma...Baosteel＇ s Slag Short Flow（BSSF） is an innovative process for steelmaking slag treatment that was developed by Baosteel. The process principles, flow-chart, parameters and component systems of the BSSF for steelmaking slag treatment are presented. Characteristics of the finished BSSF slag are summarized by analyzing the slag＇ s physical and chemical performances. Several Utilization methods for the BSSF slag are given.展开更多
Traffic flow prediction in urban areas is essential in the IntelligentTransportation System (ITS). Short Term Traffic Flow (STTF) predictionimpacts traffic flow series, where an estimation of the number of vehicleswil...Traffic flow prediction in urban areas is essential in the IntelligentTransportation System (ITS). Short Term Traffic Flow (STTF) predictionimpacts traffic flow series, where an estimation of the number of vehicleswill appear during the next instance of time per hour. Precise STTF iscritical in Intelligent Transportation System. Various extinct systems aim forshort-term traffic forecasts, ensuring a good precision outcome which was asignificant task over the past few years. The main objective of this paper is topropose a new model to predict STTF for every hour of a day. In this paper,we have proposed a novel hybrid algorithm utilizing Principal ComponentAnalysis (PCA), Stacked Auto-Encoder (SAE), Long Short Term Memory(LSTM), and K-Nearest Neighbors (KNN) named PALKNN. Firstly, PCAremoves unwanted information from the dataset and selects essential features.Secondly, SAE is used to reduce the dimension of input data using onehotencoding so the model can be trained with better speed. Thirdly, LSTMtakes the input from SAE, where the data is sorted in ascending orderbased on the important features and generates the derived value. Finally,KNN Regressor takes information from LSTM to predict traffic flow. Theforecasting performance of the PALKNN model is investigated with OpenRoad Traffic Statistics dataset, Great Britain, UK. This paper enhanced thetraffic flow prediction for every hour of a day with a minimal error value.An extensive experimental analysis was performed on the benchmark dataset.The evaluated results indicate the significant improvement of the proposedPALKNN model over the recent approaches such as KNN, SARIMA, LogisticRegression, RNN, and LSTM in terms of root mean square error (RMSE)of 2.07%, mean square error (MSE) of 4.1%, and mean absolute error (MAE)of 2.04%.展开更多
【目的】针对高浑浊度矿井水处理技术存在处理工序长、超滤(UF)膜进水水质要求高、膜污染严重的问题,采用短流程超滤膜化学反应器(MCR)组器处理高浑浊度矿井水。【方法】在保留短流程超滤MCR工艺精简、集成度高、占地面积小的优势基础上...【目的】针对高浑浊度矿井水处理技术存在处理工序长、超滤(UF)膜进水水质要求高、膜污染严重的问题,采用短流程超滤膜化学反应器(MCR)组器处理高浑浊度矿井水。【方法】在保留短流程超滤MCR工艺精简、集成度高、占地面积小的优势基础上,对短流程超滤MCR技术的抗污染膜组器型式进行改进,探究高效膜污染控制组器型式;并对改进后组器的运行参数开展试验研究,通过优化运行通量、系统回收率、运行周期、反洗通量4个运行参数,考察不同运行条件对膜污染控制效果,从而确定抗污染膜组器的稳定运行参数,通过进水悬浮物浓度,考察短流程超滤MCR组器的进水条件。【结果】结果表明,短流程超滤MCR组器中振动模式的抗污染性能优于曝气模式,跨膜压差(TMP)低于曝气模式0.16~0.26 k Pa/d。而在振动模式中,线性振动模式TMP低于旋转振动模式0.5 k Pa/d,表明线性振动模式抗污染能力强,且线性振动模式的吨水能耗为0.03 k W·h、水阻能耗占比为28.8%,均优于旋转振动模式。此外,线性振动模式短流程超滤MCR组器在运行通量≤40L/(m^(2)·h),系统回收率≤97%,运行周期为45 min,反洗通量为60 L/(m^(2)·h)条件下,能保证膜抗污染效果,短流程超滤MCR组器进水耐受悬浮物质量浓度达到2000 mg/L,运行参数调整对产水水质无显著影响。【结论】振动模式短流程超滤MCR组器可有效减少处理工艺流程,放宽UF膜进水水质要求,缓解UF膜运行过程中膜污染的情况,可为高浑浊度矿井水工艺改造提供技术指导。展开更多
直流潮流控制器是解决环网式直流配电网的线路潮流不完全可控的有效技术手段。然而,现有方法未能充分发掘其在故障限流中的潜力。该文建立了三有源桥串并联潮流控制器(triple active bridge power flow controller,TAB-PFC)的故障模量...直流潮流控制器是解决环网式直流配电网的线路潮流不完全可控的有效技术手段。然而,现有方法未能充分发掘其在故障限流中的潜力。该文建立了三有源桥串并联潮流控制器(triple active bridge power flow controller,TAB-PFC)的故障模量分析模型,提出一种基于TAB-PFC的双极直流配电网主动限流策略。首先阐述了TAB-PFC的限流原理,提出基于TAB-PFC的主动限流控制策略。然后对TAB-PFC不同故障阶段进行建模,并计及极间互感构建含TAB-PFC的双极直流配电网故障模量等效模型。在此基础上,分析不同参数对TAB-PFC的限流能力的影响,为其参数选取提供依据。在MATLAB/Simulink搭建了含TAB-PFC的双极直流配电网模型,验证了所提主动限流策略的有效性及故障等效电路模型和参数分析的正确性。展开更多
窄路段作为交通场景中不可避免的瓶颈路段,其短时车流量预测对优化路径规划、改善交通状况具有重要意义。针对窄路段的时效性,同时考虑适用模型的准确度,提出一种基于佳点集初始化种群、非线性参数控制及柯西变异扰动的改进鲸鱼优化算法...窄路段作为交通场景中不可避免的瓶颈路段,其短时车流量预测对优化路径规划、改善交通状况具有重要意义。针对窄路段的时效性,同时考虑适用模型的准确度,提出一种基于佳点集初始化种群、非线性参数控制及柯西变异扰动的改进鲸鱼优化算法(IWOA)-门控循环单元(GRU)的窄路短时车流量预测模型,以SUMO(Simulation of Urban Mobility)仿真数据进行了实证研究。对比实验结果显示,IWOA具有较好的全局性、收敛速度且更加稳定。基于IWOA-GRU的窄路短时车流量预测模型,均方根误差(RMSE)指标相较于WOA-GRU、PSO-GRU、长短期记忆神经(LSTM)网络分别降低10.96%、28.71%、42.23%,平均绝对百分比误差(MAPE)指标分别降低13.92%、46.18%、52.83%,有较为显著的准确性和稳定性。展开更多
文摘Baosteel＇ s Slag Short Flow（BSSF） is an innovative process for steelmaking slag treatment that was developed by Baosteel. The process principles, flow-chart, parameters and component systems of the BSSF for steelmaking slag treatment are presented. Characteristics of the finished BSSF slag are summarized by analyzing the slag＇ s physical and chemical performances. Several Utilization methods for the BSSF slag are given.
文摘Traffic flow prediction in urban areas is essential in the IntelligentTransportation System (ITS). Short Term Traffic Flow (STTF) predictionimpacts traffic flow series, where an estimation of the number of vehicleswill appear during the next instance of time per hour. Precise STTF iscritical in Intelligent Transportation System. Various extinct systems aim forshort-term traffic forecasts, ensuring a good precision outcome which was asignificant task over the past few years. The main objective of this paper is topropose a new model to predict STTF for every hour of a day. In this paper,we have proposed a novel hybrid algorithm utilizing Principal ComponentAnalysis (PCA), Stacked Auto-Encoder (SAE), Long Short Term Memory(LSTM), and K-Nearest Neighbors (KNN) named PALKNN. Firstly, PCAremoves unwanted information from the dataset and selects essential features.Secondly, SAE is used to reduce the dimension of input data using onehotencoding so the model can be trained with better speed. Thirdly, LSTMtakes the input from SAE, where the data is sorted in ascending orderbased on the important features and generates the derived value. Finally,KNN Regressor takes information from LSTM to predict traffic flow. Theforecasting performance of the PALKNN model is investigated with OpenRoad Traffic Statistics dataset, Great Britain, UK. This paper enhanced thetraffic flow prediction for every hour of a day with a minimal error value.An extensive experimental analysis was performed on the benchmark dataset.The evaluated results indicate the significant improvement of the proposedPALKNN model over the recent approaches such as KNN, SARIMA, LogisticRegression, RNN, and LSTM in terms of root mean square error (RMSE)of 2.07%, mean square error (MSE) of 4.1%, and mean absolute error (MAE)of 2.04%.
文摘【目的】针对高浑浊度矿井水处理技术存在处理工序长、超滤(UF)膜进水水质要求高、膜污染严重的问题,采用短流程超滤膜化学反应器(MCR)组器处理高浑浊度矿井水。【方法】在保留短流程超滤MCR工艺精简、集成度高、占地面积小的优势基础上,对短流程超滤MCR技术的抗污染膜组器型式进行改进,探究高效膜污染控制组器型式;并对改进后组器的运行参数开展试验研究,通过优化运行通量、系统回收率、运行周期、反洗通量4个运行参数,考察不同运行条件对膜污染控制效果,从而确定抗污染膜组器的稳定运行参数,通过进水悬浮物浓度,考察短流程超滤MCR组器的进水条件。【结果】结果表明,短流程超滤MCR组器中振动模式的抗污染性能优于曝气模式,跨膜压差(TMP)低于曝气模式0.16~0.26 k Pa/d。而在振动模式中,线性振动模式TMP低于旋转振动模式0.5 k Pa/d,表明线性振动模式抗污染能力强,且线性振动模式的吨水能耗为0.03 k W·h、水阻能耗占比为28.8%,均优于旋转振动模式。此外,线性振动模式短流程超滤MCR组器在运行通量≤40L/(m^(2)·h),系统回收率≤97%,运行周期为45 min,反洗通量为60 L/(m^(2)·h)条件下,能保证膜抗污染效果,短流程超滤MCR组器进水耐受悬浮物质量浓度达到2000 mg/L,运行参数调整对产水水质无显著影响。【结论】振动模式短流程超滤MCR组器可有效减少处理工艺流程,放宽UF膜进水水质要求,缓解UF膜运行过程中膜污染的情况,可为高浑浊度矿井水工艺改造提供技术指导。
文摘直流潮流控制器是解决环网式直流配电网的线路潮流不完全可控的有效技术手段。然而,现有方法未能充分发掘其在故障限流中的潜力。该文建立了三有源桥串并联潮流控制器(triple active bridge power flow controller,TAB-PFC)的故障模量分析模型,提出一种基于TAB-PFC的双极直流配电网主动限流策略。首先阐述了TAB-PFC的限流原理,提出基于TAB-PFC的主动限流控制策略。然后对TAB-PFC不同故障阶段进行建模,并计及极间互感构建含TAB-PFC的双极直流配电网故障模量等效模型。在此基础上,分析不同参数对TAB-PFC的限流能力的影响,为其参数选取提供依据。在MATLAB/Simulink搭建了含TAB-PFC的双极直流配电网模型,验证了所提主动限流策略的有效性及故障等效电路模型和参数分析的正确性。
文摘窄路段作为交通场景中不可避免的瓶颈路段,其短时车流量预测对优化路径规划、改善交通状况具有重要意义。针对窄路段的时效性,同时考虑适用模型的准确度,提出一种基于佳点集初始化种群、非线性参数控制及柯西变异扰动的改进鲸鱼优化算法(IWOA)-门控循环单元(GRU)的窄路短时车流量预测模型,以SUMO(Simulation of Urban Mobility)仿真数据进行了实证研究。对比实验结果显示,IWOA具有较好的全局性、收敛速度且更加稳定。基于IWOA-GRU的窄路短时车流量预测模型,均方根误差(RMSE)指标相较于WOA-GRU、PSO-GRU、长短期记忆神经(LSTM)网络分别降低10.96%、28.71%、42.23%,平均绝对百分比误差(MAPE)指标分别降低13.92%、46.18%、52.83%,有较为显著的准确性和稳定性。
