Computer Science
Neural Network Model
100%
Feedforward Network
75%
Feature Selection
60%
Feature Extraction
60%
Deep Learning Method
60%
Support Vector Regression
50%
Series Prediction
50%
Deep Learning Model
50%
Functional Data Analysis
50%
Activation Function
45%
Time Series Data
43%
Multivariate Time Series
33%
Artificial Neural Network
30%
Feedforward Neural Network
25%
Simulation Study
25%
Exponential Smoothing
25%
Deep Neural Network
20%
Spatial Information
16%
Multiple Time Series
16%
Production Unit
10%
Root Mean Squared Error
10%
Selection Criterion
10%
Logistic Sigmoid
10%
Prediction Accuracy
10%
Leaning Parameter
10%
Individual Variable
10%
Data Analysis Approach
10%
Engineering
Feedforward
83%
Hidden Layer
83%
Deep Learning Method
62%
Network Model
58%
Quantile Regression Neural Network
50%
Electricity Consumption
50%
Roll Motion
50%
Design of Experiments
50%
Appliance Energy
50%
Activation Function
41%
Artificial Neural Network Model
37%
Deep Neural Network
25%
Natural Gas
16%
Electrical Energy
16%
Energy Engineering
16%
Electricity Demand
16%
Industrial Development
16%
Nonlinearity
16%
Data Series
12%
Good Prediction
12%
Production Unit
12%
Nodes
12%
Selection Criterion
12%
Feature Extraction
12%
Root-Mean-Squared Error
12%
Input Feature
12%
Model Data
10%
Neural Network Approach
10%
Real Data
10%
Hybrid Method
10%
Quantile
10%
Mathematics
Support Vector Machine
50%
Autoregressive Integrated Moving Average
50%
Autoregressive Integrated Moving Average Model
50%
Artificial Neural Network
50%
Deep Learning Method
50%
Functional Data
50%
Autoregressive Model
33%
Time Series Data
33%
Time Series Modeling
16%
Time Series Forecasting
14%
Deep Neural Network
14%
Individual Variable
12%
Network Model
7%
Production Unit
7%
Time Series Analysis
7%
Linear Models
7%
Nonlinear Model
7%
