Keyphrases
Artificial Neural Network
66%
Weather Prediction
33%
Weather Conditions
33%
Drought Prediction
33%
Standardized Precipitation Index
33%
PM10
33%
Jakarta
33%
Particulate Matter 2.5 (PM2.5)
33%
Prediction Method
33%
Multilayer Perceptron
33%
Fengyun-4A (FY-4A)
25%
SPI-3
25%
SPI1
25%
Air Quality
25%
Surabaya
22%
Air Pressure
19%
Error Value
19%
Wind Speed
19%
Rainfall
19%
Historical Data
16%
Efficiency Value
16%
Drought
16%
Indonesia
16%
Nash-Sutcliffe Efficiency
16%
Hourly Wind Speed
11%
Weather Forecast
11%
Forecaster
11%
Safety Development
11%
Intelligence Artificial
11%
Technology Intelligence
11%
Future Weather
11%
Rainfall Intensity
11%
Neural Network Algorithm
11%
Transportation Safety
11%
Training Data
11%
Artificial Intelligence
11%
Artificial Neural Network Model
11%
Artificial Intelligence Technology
11%
Humidity
11%
Feedforward Neural Network
11%
Best Model
11%
Meteorological Station
11%
Technology Development
11%
Air Quality Prediction
8%
Forecasting Modeling
8%
Hydrological Aspects
8%
Rainfall Accumulation
8%
PM10 Concentration
8%
Rainfall Data
8%
Information-centric
8%
INIS
prediction
100%
neural networks
66%
data
50%
implementation
33%
precipitation
33%
weather
33%
range
33%
droughts
33%
air quality
33%
layers
33%
values
20%
modeling
20%
air
19%
speed
19%
wind
19%
indonesia
16%
forecasting
13%
humidity
13%
information
12%
artificial intelligence
11%
errors
9%
performance
9%
algorithms
9%
levels
8%
comparative evaluations
8%
solutions
8%
sun
8%
increasing
8%
concentration
8%
fluctuations
7%
efficiency
7%
meteorology
5%
safety
5%
correlations
5%
architecture
5%
Engineering
Artificial Neural Network
66%
Particular Matter 2.5
33%
Perceptron
33%
Air Quality
26%
Artificial Intelligence
22%
Sutcliffe
22%
Efficiency Value
22%
Error Value
22%
Atmospheric Pressure
17%
Historical Data
13%
Forecaster
11%
Artificial Neural Network Model
11%
Feedforward
11%
Good Performance
11%
Span Increase
11%
Rain Gage
11%
Actual Value
11%
Root Mean Square Error
11%
Prediction Performance
11%
Quality Information
6%