Keyphrases
Machine Learning Approach
100%
Atchafalaya River
100%
Mississippi-Atchafalaya River
100%
Nutrient Yield
100%
Nutrient Loading
55%
Principal Coordinate Analysis (PCoA)
44%
Excess nutrients
33%
Clustering Analysis
33%
Yield Distribution
33%
T-distributed Stochastic Neighbor Embedding (t-SNE)
33%
United States Geological Survey
22%
Gulf of Mexico
22%
High-dimensional Data
22%
Water Station
22%
Dimensionality Reduction
11%
Population Density
11%
Silica
11%
Pollution Control
11%
Effective Tool
11%
Eutrophication
11%
Machine Learning
11%
Hypoxia
11%
Nutrient Concentration
11%
Phosphorus
11%
Annual Mean
11%
Major Contributor
11%
Management Control
11%
Mississippi River
11%
Main Components
11%
Surface Water Quality
11%
Water Quality Indicators
11%
Orthophosphate
11%
Clustering Results
11%
Total Variance
11%
Fundamental Causes
11%
Industrial Discharge
11%
Domestic Discharges
11%
Consistent Clustering
11%
River Basin Area
11%
Local Structure
11%
Nitrogen Yield
11%
Load Management
11%
Neighbor Clustering
11%
Crop Density
11%
Monitoring Station
11%
Hypoxic Zone
11%
Total Suspended Sediment
11%
Nonlinear Structures
11%
Earth and Planetary Sciences
River Basin
100%
Machine Learning
100%
Mississippi
100%
Principal Component Analysis
40%
Geological Survey
20%
Gulf of Mexico
20%
Spatial Variation
10%
Pollution Control
10%
Surface Water
10%
Temporal Variation
10%
Eutrophication
10%
Suspended Sediment
10%
Orthophosphate
10%
Nitrogen Dioxide
10%
Water Quality Indicator
10%
Monitoring Station
10%