A support vector machine (SVM) forecasting model based on rough set (RS) data preprocess was proposed by combining the rough set attribute reduction and the support vector machine regression algorithm, because there a...A support vector machine (SVM) forecasting model based on rough set (RS) data preprocess was proposed by combining the rough set attribute reduction and the support vector machine regression algorithm, because there are strong complementarities between two models. Firstly, the rough set was used to reduce the condition attributes, then to eliminate the attributes that were redundant for the forecast, Secondly, it adopted the minimum condition attributes obtained by reduction and the corresponding original data to re-form a new training sample, which only kept the important attributes affecting the forecast accuracy. Finally, it studied and trained the SVM with the training samples after reduction, inputted the test samples re-formed by the minimum condition attributes and the corresponding original data, and then got the mapping relationship model between condition attributes and forecast variables after testing it. This model was used to forecast the power supply and demand. The results show that the average absolute error rate of power consumption of the whole society and yearly maximum load are 14.21% and 13.23%, respectively, which indicates that the RS-SVM forecast model has a higher degree of accuracy.展开更多
The development situation of the polyolefin industry during the first four years of the Elevemth Five-year-plan was reviewed.Domestic supply and demand of polyolefins at the period of the Twelfth Five-year-plan were a...The development situation of the polyolefin industry during the first four years of the Elevemth Five-year-plan was reviewed.Domestic supply and demand of polyolefins at the period of the Twelfth Five-year-plan were analyzed and predicted.It was pointed out that production capacity of polyolefin in China will be increased significantly and market demand will keep a steady growth.Large-scale industrial equipment of polyolefin will be developed to meet the increasing demand.展开更多
以北京市四惠枢纽为研究对象,探索以数据驱动为导向满足乘客需求的枢纽动态导向标识方案评估及优化设计方法。首先,搭建KANO乘客需求模型,通过桌面实验,形成动态导向标识在内容、样式及空间位置上的优化设计方案,与四惠枢纽现有方案形...以北京市四惠枢纽为研究对象,探索以数据驱动为导向满足乘客需求的枢纽动态导向标识方案评估及优化设计方法。首先,搭建KANO乘客需求模型,通过桌面实验,形成动态导向标识在内容、样式及空间位置上的优化设计方案,与四惠枢纽现有方案形成对比。其次,基于寻路理论通过建筑信息建模(building information modeling,BIM)+虚拟现实(virtual reality,VR)仿真技术,实现人与枢纽的信息交互,提取新旧导向标识方案作用下乘客寻路过程的特征参数。最后,通过对寻路实验中主客观指标分析可知,被试在新版动态导向标识方案中寻路时间、犯错误点数及迷茫点数显著降低,且新版动态导向标识方案在内容、样式及空间位置上满意度均优于旧版。结果表明:研究搭建BIM+VR的虚拟仿真平台,形成以数据驱动为导向的枢纽动态导向标识方案综合评估及优化设计方法,为枢纽动态导向标识方案设计及合理应用提供技术与理论支撑。展开更多
基金Project(70901025) supported by the National Natural Science Foundation of China
文摘A support vector machine (SVM) forecasting model based on rough set (RS) data preprocess was proposed by combining the rough set attribute reduction and the support vector machine regression algorithm, because there are strong complementarities between two models. Firstly, the rough set was used to reduce the condition attributes, then to eliminate the attributes that were redundant for the forecast, Secondly, it adopted the minimum condition attributes obtained by reduction and the corresponding original data to re-form a new training sample, which only kept the important attributes affecting the forecast accuracy. Finally, it studied and trained the SVM with the training samples after reduction, inputted the test samples re-formed by the minimum condition attributes and the corresponding original data, and then got the mapping relationship model between condition attributes and forecast variables after testing it. This model was used to forecast the power supply and demand. The results show that the average absolute error rate of power consumption of the whole society and yearly maximum load are 14.21% and 13.23%, respectively, which indicates that the RS-SVM forecast model has a higher degree of accuracy.
文摘The development situation of the polyolefin industry during the first four years of the Elevemth Five-year-plan was reviewed.Domestic supply and demand of polyolefins at the period of the Twelfth Five-year-plan were analyzed and predicted.It was pointed out that production capacity of polyolefin in China will be increased significantly and market demand will keep a steady growth.Large-scale industrial equipment of polyolefin will be developed to meet the increasing demand.
文摘以北京市四惠枢纽为研究对象,探索以数据驱动为导向满足乘客需求的枢纽动态导向标识方案评估及优化设计方法。首先,搭建KANO乘客需求模型,通过桌面实验,形成动态导向标识在内容、样式及空间位置上的优化设计方案,与四惠枢纽现有方案形成对比。其次,基于寻路理论通过建筑信息建模(building information modeling,BIM)+虚拟现实(virtual reality,VR)仿真技术,实现人与枢纽的信息交互,提取新旧导向标识方案作用下乘客寻路过程的特征参数。最后,通过对寻路实验中主客观指标分析可知,被试在新版动态导向标识方案中寻路时间、犯错误点数及迷茫点数显著降低,且新版动态导向标识方案在内容、样式及空间位置上满意度均优于旧版。结果表明:研究搭建BIM+VR的虚拟仿真平台,形成以数据驱动为导向的枢纽动态导向标识方案综合评估及优化设计方法,为枢纽动态导向标识方案设计及合理应用提供技术与理论支撑。
