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We developed a mathematical model using a Markov approach, with a six month time step to evaluate the cost effectiveness of alternative options.
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Surprisingly, in many earlier studies, only 1-month time step has been used.
The demographic module determines the population structure, by age and sex, with a one month time-step for evolution in time.
Provision of month-time step assessments is expected to improve understanding of erosion processes, especially in relation to land uses and climate change.
Time integration is performed over 48 h from 0000 UTC 19 February, 2009 with a time step of 10 s.
In model (1.1), is the population density of the species at n th time step (year, month, day), represents the intrinsic growth rate of species at n th time step, and reflects the interspecific or intraspecific competitive intensity of species to species with time delay at n th time step.
Here we approximate one time step as one month given past data calibration (Abdollahian et al. 2012) for a simulated time span of almost 60 years.
The tests are executed on an IBM dual processors computer operating at 2.5 GHz with 4 GB RAM under 32-bit Windows 7. The time horizon of the mid-term scheduling is 1 year, and the time step is 1 month.
The model uses a discrete time step of 1 month.
The time step of the model was one month, which reflects a realistic time scale for control actions.
The modeling system was developed based on a daily time step using a growing season simulation period running from April through September each year.
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