针对传统城市道路信息集成系统应用效果不佳的问题,提出基于地理信息系统(Geographic Information System,GIS)的城市道路信息集成系统。首先,将数据分为GIS空间数据与GIS属性数据,建立基于GIS的城市道路信息系统数据架构;其次,设置GIS...针对传统城市道路信息集成系统应用效果不佳的问题,提出基于地理信息系统(Geographic Information System,GIS)的城市道路信息集成系统。首先,将数据分为GIS空间数据与GIS属性数据,建立基于GIS的城市道路信息系统数据架构;其次,设置GIS查询统计模块用于分析数据,设置GIS自动计算模块用于提供平面的道路交通信息,设置GIS排版输出模块用于显示结果;最后,进行实验分析。实验结果表明:该系统的监测误差小于2%,车辆速度比例分布趋势与实际车辆速度基本一致,具有良好的应用性能。展开更多
In the era of intelligent economy, the click-through rate(CTR) prediction system can evaluate massive service information based on user historical information, and screen out the products that are most likely to be fa...In the era of intelligent economy, the click-through rate(CTR) prediction system can evaluate massive service information based on user historical information, and screen out the products that are most likely to be favored by users, thus realizing customized push of information and achieve the ultimate goal of improving economic benefits. Sequence modeling is one of the main research directions of CTR prediction models based on deep learning. The user's general interest hidden in the entire click history and the short-term interest hidden in the recent click behaviors have different influences on the CTR prediction results, which are highly important. In terms of capturing the user's general interest, existing models paid more attention to the relationships between item embedding vectors(point-level), while ignoring the relationships between elements in item embedding vectors(union-level). The Lambda layer-based Convolutional Sequence Embedding(LCSE) model proposed in this paper uses the Lambda layer to capture features from click history through weight distribution, and uses horizontal and vertical filters on this basis to learn the user's general preferences from union-level and point-level. In addition, we also incorporate the user's short-term preferences captured by the embedding-based convolutional model to further improve the prediction results. The AUC(Area Under Curve) values of the LCSE model on the datasets Electronic, Movie & TV and MovieLens are 0.870 7, 0.903 6 and 0.946 7, improving 0.45%, 0.36% and 0.07% over the Caser model, proving the effectiveness of our proposed model.展开更多
目的了解家长为儿童接种非免疫规划(Expanded Program on Immunization,EPI)疫苗的意愿,分析接种疫苗收益和风险感知对接种意愿的影响。方法2019年12月至2020年1月选择中国6个省份12个区县34个预防接种门诊0-3岁儿童家长,开展接种疫苗...目的了解家长为儿童接种非免疫规划(Expanded Program on Immunization,EPI)疫苗的意愿,分析接种疫苗收益和风险感知对接种意愿的影响。方法2019年12月至2020年1月选择中国6个省份12个区县34个预防接种门诊0-3岁儿童家长,开展接种疫苗收益和风险感知和非EPI疫苗接种意愿问卷调查。采用Logistic回归模型分析儿童家长接种疫苗收益和风险感知对接种意愿的影响。结果本研究纳入儿童家长3030名,其中感知到接种疫苗收益、风险的家长分别占88.38%、60.51%,71.16%的家长愿意为儿童接种非EPI疫苗。Logistic回归分析显示,与未感知接种疫苗收益和风险的儿童家长相比,同时感知收益和风险、仅感知收益、仅感知风险的儿童家长的接种意愿高[OR(95%CI):7.03(5.05-9.77)、5.49(3.91-7.71)、2.02(1.30-3.16)]。结论家长对儿童接种非EPI疫苗普遍持接受态度,接种疫苗收益和风险感知影响接种意愿;应加强儿童家长的非EPI疫苗预防接种知识宣传。展开更多
文摘针对传统城市道路信息集成系统应用效果不佳的问题,提出基于地理信息系统(Geographic Information System,GIS)的城市道路信息集成系统。首先,将数据分为GIS空间数据与GIS属性数据,建立基于GIS的城市道路信息系统数据架构;其次,设置GIS查询统计模块用于分析数据,设置GIS自动计算模块用于提供平面的道路交通信息,设置GIS排版输出模块用于显示结果;最后,进行实验分析。实验结果表明:该系统的监测误差小于2%,车辆速度比例分布趋势与实际车辆速度基本一致,具有良好的应用性能。
基金Supported by the National Natural Science Foundation of China (62272214)。
文摘In the era of intelligent economy, the click-through rate(CTR) prediction system can evaluate massive service information based on user historical information, and screen out the products that are most likely to be favored by users, thus realizing customized push of information and achieve the ultimate goal of improving economic benefits. Sequence modeling is one of the main research directions of CTR prediction models based on deep learning. The user's general interest hidden in the entire click history and the short-term interest hidden in the recent click behaviors have different influences on the CTR prediction results, which are highly important. In terms of capturing the user's general interest, existing models paid more attention to the relationships between item embedding vectors(point-level), while ignoring the relationships between elements in item embedding vectors(union-level). The Lambda layer-based Convolutional Sequence Embedding(LCSE) model proposed in this paper uses the Lambda layer to capture features from click history through weight distribution, and uses horizontal and vertical filters on this basis to learn the user's general preferences from union-level and point-level. In addition, we also incorporate the user's short-term preferences captured by the embedding-based convolutional model to further improve the prediction results. The AUC(Area Under Curve) values of the LCSE model on the datasets Electronic, Movie & TV and MovieLens are 0.870 7, 0.903 6 and 0.946 7, improving 0.45%, 0.36% and 0.07% over the Caser model, proving the effectiveness of our proposed model.
文摘目的了解家长为儿童接种非免疫规划(Expanded Program on Immunization,EPI)疫苗的意愿,分析接种疫苗收益和风险感知对接种意愿的影响。方法2019年12月至2020年1月选择中国6个省份12个区县34个预防接种门诊0-3岁儿童家长,开展接种疫苗收益和风险感知和非EPI疫苗接种意愿问卷调查。采用Logistic回归模型分析儿童家长接种疫苗收益和风险感知对接种意愿的影响。结果本研究纳入儿童家长3030名,其中感知到接种疫苗收益、风险的家长分别占88.38%、60.51%,71.16%的家长愿意为儿童接种非EPI疫苗。Logistic回归分析显示,与未感知接种疫苗收益和风险的儿童家长相比,同时感知收益和风险、仅感知收益、仅感知风险的儿童家长的接种意愿高[OR(95%CI):7.03(5.05-9.77)、5.49(3.91-7.71)、2.02(1.30-3.16)]。结论家长对儿童接种非EPI疫苗普遍持接受态度,接种疫苗收益和风险感知影响接种意愿;应加强儿童家长的非EPI疫苗预防接种知识宣传。
