Integrated spatio‐temporal data mining for forest fire prediction
Forests play a critical role in sustaining the human environment. Most forest fires not only
destroy the natural environment and ecological balance, but also seriously threaten the …
destroy the natural environment and ecological balance, but also seriously threaten the …
Using multiple time series analysis for geosensor data forecasting
Forecasting in geophysical time series is a challenging problem with numerous applications.
The presence of correlation (ie spatial correlation across several sites and time correlation …
The presence of correlation (ie spatial correlation across several sites and time correlation …
Spatiotemporal data mining
M Nanni, B Kuijpers, C Körner, M May… - Mobility, data mining and …, 2008 - Springer
After the introduction and development of the relational database model between 1970 and
the 1980s, this model proved to be insufficiently expressive for specific applications dealing …
the 1980s, this model proved to be insufficiently expressive for specific applications dealing …
Stiff: A forecasting framework for spatiotemporal data
Z Li, MH Dunham, Y Xiao - Mining Multimedia and Complex Data: KDD …, 2003 - Springer
Nowadays spatiotemporal forecasting has been drawing more and more attention from
academic researchers and industrial practitioners for its promising applicability to complex …
academic researchers and industrial practitioners for its promising applicability to complex …
时空预测技术在森林防火中的应用研究
王佳璆， 程涛 - 中山大学学报: 自然科学版, 2007 - cqvip.com
构建了一个随机的时间序列模型获得每一个空间上相互独立部分的时间预测,
然后建立动态回归神经网络(DRNN) 发现隐藏的空间关系, 最后用统计回归方法把单个时间和 …
然后建立动态回归神经网络(DRNN) 发现隐藏的空间关系, 最后用统计回归方法把单个时间和 …
A tensor framework for geosensor data forecasting of significant societal events
Geosensor data forecasting has high practical value in government affairs such as prompt
response and decision making. However, the spatial correlation across distinct sites and the …
response and decision making. However, the spatial correlation across distinct sites and the …
A new method of railway passenger flow forecasting based on spatio-temporal data mining
W Xu, Y Qin, H Huang - Proceedings. The 7th International …, 2004 - ieeexplore.ieee.org
By analyzing the limitation of current passenger flow forecasting approach, This work
presents a new approach to forecast the railway passenger flow based on spatio-temporal …
presents a new approach to forecast the railway passenger flow based on spatio-temporal …
Modeling spatial-temporal data with a short observation history
D Pokrajac, RL Hoskinson, Z Obradovic - Knowledge and information …, 2003 - Springer
A novel method is proposed for forecasting spatial-temporal data with a short observation
history sampled on a uniform grid. The method is based on spatial-temporal autoregressive …
history sampled on a uniform grid. The method is based on spatial-temporal autoregressive …
面向移动环境的时空数据挖掘研究现状与展望
陈捷， 唐世渭， 杨冬青， 王腾蛟 - 计算机工程与应用, 2002 - cqvip.com
移动通信与无线定位技术的迅速发展导致了大量时空数据的产生. 面向移动环境的时空数据挖掘
的目标就是从这些数据中抽取知识, 为基于位置的服务, 智能交通系统等提供有效的决策支持 …
的目标就是从这些数据中抽取知识, 为基于位置的服务, 智能交通系统等提供有效的决策支持 …