1. Calibration And Validation Model
Presented By:-
Rajan Kandel
http://rajankandel.com.np

2. Introduction
Calibration

Its an iterative process of comparing the model to
real system.

Makes Adjustments to the model.

Done until model imitates the real system.

3. Contd..

Checks that the data generated by the simulation
matches real (observed) data.

A tweaking/tuning of existing parameters and
usually

Does not involve the introduction of new ones,
changing the model structure.

4. Contd..
Initiate ModelInitiate Model
Real
System
Real
System
Compare model to
real system
First Revision
of
model
First Revision
of
model
Revised
Revised
Second
Revision
of model
Second
Revision
of model
Compare model to
real system
Fig: Calibration of Model

5. Calibration Issues

Very Important For Model Accuracy and
Robustness

Accuracy Depends on Measurement Granularity

Averages Over Several Days is a Bad Choice

Might Need Additional Information to be
collected in Turbulent Sections

6. Calibration Issues

Simulation Objective Affects Calibration

When Adaptive Control Strategies Are Simulated,

Stricter Validation is Needed

Modeling of an Isolated Interchange in Rural

Very time consuming process

7. Things to be considered Before
Calibration

Check Geometry For Correctness

Disjoined Sections

Stuck Vehicles (Sizes of Accel/Decel Lanes)

Verify Location of Detectors

Check Input For Accuracy

Entrance Volume Comparison (Perfect
Match)

Volume Totals on Mainline Stations Should
Match

8. Introduction
Validation

Check whether the model is valid

If not valid, then any conclusions derived from it is
of virtually no value.

Validation and verification are two of the most
important steps

9. Techniques for Verification of
Simulation Models

Use good programming practice:

Write and debug the computer program in
modules or subprograms.

It is better to start with a “moderately detailed”
model, and later embellish, if needed.

Use “structured walk-through”:

Have more than one person to read the
computer program.

10. contd..

Check simulation output for reasonableness:

Run the simulation model for a variety of input
scenarios and check to see if the output is
reasonable.

In some instances, certain measures of
performance can be computed exactly and used for
comparison.

Animate:

Using animation, the users see dynamic displays
(moving pictures) of the simulated system.

Since the users are familiar with the real system,
they can detect programming and conceptual
errors.

11. Steps In Model validation

Naylor & Finger(1967) Formulated three steps in
model validation
1) Build a model that has high face validity
2) validate model assumption.
3) compare the model input-output
transformation to corresponding input-output of
real system.

12. Face Validity
 Construct a model that appears reasonable on its
face to its users
 User of model must be involved in model
construction from its conceptualization to its
implementation

13. Validity of Model Assumption
 Divided into 2 categories:
• Structural Assumption
How system operates
Involves simplification and abstraction
of reality
• Data Assumption
Based on collection of reliable data
And correct statistical analysis of data

14. Validity of Input-Output
transformation
 Accepts values of input parameters and
transforms into output
 The modeler can use historical data
X Uncontrolled Variable
D Decision Variable
Y Output
(X,D) output
*f=transformation operation
f*

15. Thank You