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Using artificial intelligence to find anomalies hiding in massive datasets（图）
人工智能 数据集 机器学习技术 电网故障
2023/6/20
Identifying a malfunction in the nation’s power grid can be like trying to find a needle in an enormous haystack. Hundreds of thousands of interrelated sensors spread across the U.S. capture data on e...
2017金融和经济数据集与宏观建模数据科学国际研讨会（International Workshop on Data Science for Macro-Modeling with Financial and Economic Datasets）
2017 金融 经济数据集 宏观建模 数据科学 国际研讨会
2017/4/10
The promise of Big Data, linked data and social data is the availability of large scale yet granular datasets to support modeling of complex ecosystems reflecting cyber-human decision making. While co...
Changes in Workplace Segregation in the United States: Evidence from the 1990 and 2000 Decennial Employer-Employee Datasets
segregation education race ethnicity sex
2015/9/18
We present evidence on changes in workplace segregation by education, race, ethnicity, and sex,
from 1990 to 2000. The evidence indicates that racial and ethnic segregation at the workplace level
re...
ESSG-BASED GLOBAL SPATIAL REFERENCE FRAME FOR DATASETS INTERRELATION
global spatial reference frame earth system spatial grid SDOG-R interrelation coordinate transformation
2014/4/21
To know well about the highly complex earth system, a large volume of, as well as a large variety of, datasets on the planet Earth are
being obtained, distributed, and shared worldwide everyday. How...
Merged Datasets: AN ANALYTIC TOOL FOR EVIDENCE-BASED MANAGEMENT
information on the usefulness of merging joining datasets evidence-based management evidence-based management techniques
2011/10/8
The article presents information on the usefulness of merging or joining datasets as a method for evidence-based management. The process of creating such a dataset is described as merging, indexing, c...
Detecting and handling outlying trajectories in irregularly sampled functional datasets
outlying trajectories sampled functional datasets
2010/11/8
Outlying curves often occur in functional or longitudinal datasets,and can be very influential on parameter estimators and very hard to detect visually. In this article we introduce estimators of the ...
A Spatially-adjusted Bayesian Additive Regression Tree Model to Merge Two Datasets
BART CART Missing variables Spatial model Survey
2009/9/22
Scientic hypotheses of interest often involve variables that are not
available in a single survey. This is a common problem for researchers working
with survey data. We propose a model-based approac...
A One-Pass Sequential Monte Carlo Method for Bayesian Analysis of Massive Datasets
Sequential Monte Carlo One-Pass Massive Datasets
2009/9/21
For Bayesian analysis of massive data, Markov chain Monte Carlo (MCMC) techniques often prove infeasible due to computational resource constraints. Standard MCMC methods generally require a complete s...