Keyphrases
Fuel Consumption
100%
NO Emission
100%
Time Series Methods
100%
Consumption Emissions
100%
Fuel NO
100%
Truck Diesel Engine
100%
Medium-duty Truck
100%
NOx Emission
75%
Root Mean Square Error
75%
Bayesian Information Criterion
75%
Autoregressive Moving Average
75%
Regression Error
75%
Multiple Linear Regression
50%
Modeling Techniques
50%
ARIMAX
50%
Criterion Value
50%
Prediction Accuracy
25%
Engine Load
25%
Exhaust Gas Recirculation
25%
Internal Combustion Engine
25%
Nonlinear Autoregressive Network with Exogenous Inputs
25%
Four-stroke
25%
Diesel Engine
25%
Outlet Temperature
25%
Engine Speed
25%
Modeling Methodology
25%
Loss Cost
25%
Air Temperature
25%
Gas Pressure
25%
High Cost
25%
Intake Manifold
25%
Air Pressure
25%
Exhaust Gas
25%
Turbocharger
25%
Time Loss
25%
Time Series Modeling
25%
Moving Average Method
25%
Autoregressive Integrated Moving Average (ARIMA)
25%
External Inputs
25%
Artificial Time Series
25%
Experimental Testing
25%
Selective Catalytic Reduction
25%
Intelligent Modeling
25%
Fuel Consumption Model
25%
Engine Dynamics
25%
Passenger Bus
25%
Time Series Neural Network
25%
Variable Geometry
25%
Engine Integration
25%
Mean Square Error Criterion
25%
Integration Test
25%
NOx Emission Model
25%
Application Ability
25%
Common Rail Pressure
25%
Engine Coolant Temperature
25%
Experimental Dataset
25%
High Time
25%
Accelerator Pedal
25%
Engineering
Diesel Engine
100%
Moving Average
100%
Root Mean Square Error
75%
Input Data
25%
Internal Combustion Engine
25%
Outlet Temperature
25%
Engine Speed
25%
Regression Technique
25%
Accurate Prediction
25%
Gas Pressure
25%
Exhaust Gas Recirculation
25%
Turbocharger
25%
Selective Catalytic Reduction
25%
Exhaust Gas
25%