PROJECT GIGALOPOLIS

Prediction Mode Process Flow

Prediction mode is a collection of Monte Carlo simulations. The coefficient set and initial images for a prediction run are identical for every simulation, but the initializing seed value is altered a MONTE_CARLO_ITERATION (MC) number of times, with each simulation evolving slightly differently due to the modified random number series.

The first seed value is set in the scenario file with the RANDOM_SEED flag. The number of Monte Carlo iterations is set in the scenario file using the MONTE_CARLO_ITERATION flag. The coefficient set is defined in the scenario file with the PREDCTION_*_BEST_FIT flag, where "*" indicates a coefficient type. For a description of prediction mode output see our data page.

 

Initial Conditions

Each simulation in a prediction run is initialized with the PREDCITION_*_BEST_FIT coefficient set and SLEUTH images as described in a basic simulation. The seed value for the first simulation is initialized with the RANDOM_SEED flag. After a simulation is completed, the initializing seed that began that simulation is reset and a new simulation is run. This process continues MC number of times.

 

Growth Cycles

It is assumed that one growth cycle represents a year of growth. Following this assumption:

number of growth cycles in a simulation = stop_date - start_date.


Conclude Simulation

When the required number of growth cycles has been generated, the simulation

 

 

 


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