以旅游大数据为基础,考虑长时间范围内的滞后效应以及不同搜索强度指数(Search Intensity Index,SII)之间的多任务影响,提出一种基于大数据的多任务旅游信息分析(Multi-tasking Tourism Information Analysis Based on Big Data,MTIABD...以旅游大数据为基础,考虑长时间范围内的滞后效应以及不同搜索强度指数(Search Intensity Index,SII)之间的多任务影响,提出一种基于大数据的多任务旅游信息分析(Multi-tasking Tourism Information Analysis Based on Big Data,MTIABD)框架。使用融合信息重排序技术预测旅游需求,具体根据图引导结构模拟历史变量对未来变量的滞后影响。每个变量通过时间维度上的卷积神经网络(Convolutional Neural Network,CNN)进行独立编码,利用二分图动态建模滞后效应,通过图聚合进行挖掘,实现对旅游需求的精准预测。基于上述技术,构建旅游需求预测系统,旅游者能够根据需求检索不同景点的信息。在真实数据集上进行大量实验,结果表明所提出的MTIABD框架在一步和多步预测方面均优于现有方法。在平均绝对百分比误差(Mean Absolute Percentage Error,MAPE)指标下,相较于基于实例的多变量时间序列图预测框架(Instance-wise Graph-rased Framework for Multivariate Time Series Forecasting,IGMTF),MTIABD在HK-2021数据集上的性能提高了16.75%,在MO-2021数据集上的性能提高了19.79%。展开更多
Two building factors-a longer thermal lag of more than one hour for building envelops and a lag of indoor radiation to convert into cooling load-have impact on the instantaneous heat input and instantaneous cooling lo...Two building factors-a longer thermal lag of more than one hour for building envelops and a lag of indoor radiation to convert into cooling load-have impact on the instantaneous heat input and instantaneous cooling load.So the two factors should be taken into account when selecting the weather parameters for air-conditioning system design.This paper developed a new statistic method for the rational selection of coincident solar irradiance,dry-bulb and wet-bulb temperatures.The method was applied to historic weather records of 25 years in Hong Kong to generate coincident design weather data.And the results show that traditional design solar irradiance,dry-bulb and wet-bulb temperatures may be significantly overestimated in many conditions,and the design weather data for the three different constructions is not kept constant.展开更多
Recently, lots of smoothing techniques have been presented for maneuvering target tracking. Interacting multiple model-probabilistic data association （IMM-PDA） fixed-lag smoothing algorithm provides an efficient sol...Recently, lots of smoothing techniques have been presented for maneuvering target tracking. Interacting multiple model-probabilistic data association （IMM-PDA） fixed-lag smoothing algorithm provides an efficient solution to track a maneuvering target in a cluttered environment. Whereas, the smoothing lag of each model in a model set is a fixed constant in traditional algorithms. A new approach is developed in this paper. Although this method is still based on IMM-PDA approach to a state augmented system, it adopts different smoothing lag according to diverse degrees of complexity of each model. As a result, the application is more flexible and the computational load is reduced greatly. Some simulations were conducted to track a highly maneuvering target in a cluttered environment using two sensors. The results illustrate the superiority of the proposed algorithm over comparative schemes, both in accuracy of track estimation and the computational load.展开更多
城市节律可为观察和理解城市提供一种新的模式,为当代城市问题提供新的研究视角。城市居民出行时空行为呈现明显的节律特征,其一定程度反映出城市运行的复杂性,是城市地理和行为地理研究的重要问题之一。本研究引入城市节律这一概念,关...城市节律可为观察和理解城市提供一种新的模式,为当代城市问题提供新的研究视角。城市居民出行时空行为呈现明显的节律特征,其一定程度反映出城市运行的复杂性,是城市地理和行为地理研究的重要问题之一。本研究引入城市节律这一概念,关注居民非通勤出行时空行为,以交通小区为空间单元,利用手机信令数据和POI(Point of interest)数据,基于模糊C均值(Fuzzy C-Means Clustering,FCM)的时间序列软聚类方法和空间分析有机结合,探索居民非通勤出行活动节律模式;同时利用空间滞后模型揭示了出行节律模式隶属度的影响因素。结果表明:北京居民非通勤出行节律存在7种模式,根据不同模式区域的POI的频数密度和富集指数差异,可以将7种模式描述为:“居住导向型”“商业活动型”“商务导向型”“混合偏居住型”“混合偏商务型”“科教文化型”和“休闲娱乐型”。研究发现,不同模式的平均隶属度差异较大,影响因子也存在较大差异。在北京六环内非通勤出行节律模式混合度高,且不同模式的出行节律周期、功能特征和空间分布存在较大差异。此外,出行节律存在显著的空间依赖,并与城市商业、就业、居住等城市功能结构具有较强的相关性。本研究从时空融合视角对北京居民非通勤出行节律模式进行了深入探索,研究结果有助于进一步提高人群出行节律与城市功能结构关系的科学理解,从而能够为城市规划与建设提供重要的决策支撑。展开更多
文摘以旅游大数据为基础,考虑长时间范围内的滞后效应以及不同搜索强度指数(Search Intensity Index,SII)之间的多任务影响,提出一种基于大数据的多任务旅游信息分析(Multi-tasking Tourism Information Analysis Based on Big Data,MTIABD)框架。使用融合信息重排序技术预测旅游需求,具体根据图引导结构模拟历史变量对未来变量的滞后影响。每个变量通过时间维度上的卷积神经网络(Convolutional Neural Network,CNN)进行独立编码,利用二分图动态建模滞后效应,通过图聚合进行挖掘,实现对旅游需求的精准预测。基于上述技术,构建旅游需求预测系统,旅游者能够根据需求检索不同景点的信息。在真实数据集上进行大量实验,结果表明所提出的MTIABD框架在一步和多步预测方面均优于现有方法。在平均绝对百分比误差(Mean Absolute Percentage Error,MAPE)指标下,相较于基于实例的多变量时间序列图预测框架(Instance-wise Graph-rased Framework for Multivariate Time Series Forecasting,IGMTF),MTIABD在HK-2021数据集上的性能提高了16.75%,在MO-2021数据集上的性能提高了19.79%。
文摘Two building factors-a longer thermal lag of more than one hour for building envelops and a lag of indoor radiation to convert into cooling load-have impact on the instantaneous heat input and instantaneous cooling load.So the two factors should be taken into account when selecting the weather parameters for air-conditioning system design.This paper developed a new statistic method for the rational selection of coincident solar irradiance,dry-bulb and wet-bulb temperatures.The method was applied to historic weather records of 25 years in Hong Kong to generate coincident design weather data.And the results show that traditional design solar irradiance,dry-bulb and wet-bulb temperatures may be significantly overestimated in many conditions,and the design weather data for the three different constructions is not kept constant.
基金This work is supported by the Projects of the State Key Fundamental Research (No. 2001CB309403)
文摘Recently, lots of smoothing techniques have been presented for maneuvering target tracking. Interacting multiple model-probabilistic data association （IMM-PDA） fixed-lag smoothing algorithm provides an efficient solution to track a maneuvering target in a cluttered environment. Whereas, the smoothing lag of each model in a model set is a fixed constant in traditional algorithms. A new approach is developed in this paper. Although this method is still based on IMM-PDA approach to a state augmented system, it adopts different smoothing lag according to diverse degrees of complexity of each model. As a result, the application is more flexible and the computational load is reduced greatly. Some simulations were conducted to track a highly maneuvering target in a cluttered environment using two sensors. The results illustrate the superiority of the proposed algorithm over comparative schemes, both in accuracy of track estimation and the computational load.
文摘城市节律可为观察和理解城市提供一种新的模式,为当代城市问题提供新的研究视角。城市居民出行时空行为呈现明显的节律特征,其一定程度反映出城市运行的复杂性,是城市地理和行为地理研究的重要问题之一。本研究引入城市节律这一概念,关注居民非通勤出行时空行为,以交通小区为空间单元,利用手机信令数据和POI(Point of interest)数据,基于模糊C均值(Fuzzy C-Means Clustering,FCM)的时间序列软聚类方法和空间分析有机结合,探索居民非通勤出行活动节律模式;同时利用空间滞后模型揭示了出行节律模式隶属度的影响因素。结果表明:北京居民非通勤出行节律存在7种模式,根据不同模式区域的POI的频数密度和富集指数差异,可以将7种模式描述为:“居住导向型”“商业活动型”“商务导向型”“混合偏居住型”“混合偏商务型”“科教文化型”和“休闲娱乐型”。研究发现,不同模式的平均隶属度差异较大,影响因子也存在较大差异。在北京六环内非通勤出行节律模式混合度高,且不同模式的出行节律周期、功能特征和空间分布存在较大差异。此外,出行节律存在显著的空间依赖,并与城市商业、就业、居住等城市功能结构具有较强的相关性。本研究从时空融合视角对北京居民非通勤出行节律模式进行了深入探索,研究结果有助于进一步提高人群出行节律与城市功能结构关系的科学理解,从而能够为城市规划与建设提供重要的决策支撑。
