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搜索结果: 1-15 共查到Time series data相关记录16条 . 查询时间(0.164 秒)
Aggregator oblivious encryption was proposed by Shi et al. (NDSS 2011), where an aggregator can compute an aggregated sum of data and is unable to learn anything else (aggregator obliviousness). Since...
Many satellite sensors including Landsat series have been extensively used for land cover classification. Studies have been conducted to mitigate classification problems associated with the use of sin...
The present study has developed the time series database surface soil moisture over India, for June, July and August months for the period of 20 years from 1991 to 2010, using data products generated ...
Normally, the status of land cover is inherently dynamic and changing continuously on temporal scale. However, disturbances or abnormal changes of land cover — caused by such as forest fire, flood, de...
With the advent of networking applications collecting user data on a massive scale, the privacy of individual users appears to be a major concern. The main challenge is the design of a solution that...
The El Niflo Southern Oscillation (ENSO) phenomenon produces an important inter-annual variability of oceanic and atmospheric conditions with irregular periods and amplitudes in many regions of the wo...
Long time series of satellite data provide key input for geographically explicit monitoring and modelling of the environmental condition in the context of land use and land cover change (LUCC) analys...
Preference shocks from aggregation: time series data evidence.
Periodic Time Series Data Analysis.
Vegetation responses and ecosystem function are spatially variable and influenced by climate variability. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) was used to combine MODIS ...
Abstract: We develop a scheme for estimating state-dependent drift and diffusion coefficients in a stochastic differential equation from a time-series data. There is no need to have any prior knowledg...
Vegetation responses to changing climate patterns need to be understood to devise adaptation strategy for a sustainable development, especially in the light of increasing climate related vulnerability...
In many applications, such as physiology and finance, large time series data bases are to be analyzed requiring the computation of linear, nonlinear and other measures. Such measures have been develo...
This paper studies functional coefficient regression models with nonstationary time series data, allowing also for stationary covariates. A local linear fitting scheme is developed to estimate the coe...
The discrete-time GARCH methodology which has had such a profound influence on the modelling of heteroscedasticity in time series is intuitively well motivated in capturing many `stylized facts' conce...

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