Integrative, Rapid, Data Analysis
Methods that bring together data from many sources and turn it into timely, usable insight.
-
Modeling Impacts of Irrigation on Land Surface Hydrology and Subseasonal Forecast
YN POKHREL, T YAMADA, S Shin, L Luo, D Lu, K Deb
-
Mapping Cropland and Crop-type Distribution Using Time Series MODIS Data
D Lu, Y Chen, E Moran, M Batistella, L LUO, YN POKHREL, K Deb
-
A new approach to map cropland irrigation distribution using time series remote sensing and ancillary data in a heterogeneous semi-arid and arid region: a case study in Heihe watershed
Y Chen, D Lu, J Huang, L Luo, YN POKHREL, K Deb
-
Supervised Feature Extraction of Hyperspectral Images Using Partitioned Maximum Margin Criterion
A Datta, S Ghosh, AK Ghosh. Cited by 36
-
Inferring Future Links in Large Scale Networks
S Das, SK Das, S Ghosh
-
Data mining methods for knowledge discovery in multi-objective optimization: Part B - New developments and applications
S Bandaru, AHC Ng, K Deb. Cited by 64
-
Data mining methods for knowledge discovery in multi-objective optimization: Part A - Survey
S Bandaru, AHC Ng, K Deb. Cited by 191
-
Leveraging contact pattern to predict future contact pattern in mobile networks
S Das, SK Das, S Ghosh
-
Assessing unreliability in OTT video QoE subjective evaluations using clustering with idealized data
J Jiang, P Spachos, M Chignell, L Zucherman. Cited by 4
-
Online non-negative dictionary learning via moment information for sparse Poisson coding
X Yu, H Yang, I King, MRT Lyu. Cited by 1
-
A Memetic Multi-Agent Demonstration Learning Approach with Behavior Prediction
Y Hou, Y Zeng, YS Ong. Cited by 8
-
Solving the Dynamic Vehicle Routing Problem Under Traffic Congestion
G Kim, YS Ong, T Cheong, PS Tan. Cited by 131