Based on model discussed by John D. Sterman (p 508) in All models are wrong: reflections on becoming a systems scientist (2002). Task: (A) Sketch what you think the resultant graph will be (see directions for drawing in model). (B) Then Run Simulation. Optional Extension: Replace Graph In/Out Flow connection with a connection from Trig. function. Repeat (A) & (B).
Based on model discussed by John D. Sterman (p 508) in All models are wrong: reflections on becoming a systems scientist (2002). Task: (A) Sketch what you think the resultant graph will be (see directions for drawing in model). (B) Then Run Simulation. Optional Extension: Replace Graph In/Out Flow connection with a connection from Trig. function. Repeat (A) & (B).
At first, I cloned the System Dynamics Model from the "Predator-Prey Interactions" tutorial. After I did this for populations of squirrels and mountain lions instead of moose and wolves, the model showed that the more squirrels mountain lions catch, the more the mountain lion population grows, and the squirrel population declines. The squirrel death rate, therefore, depends on the number of mountain lions and the mountain lion birth rate depends on the number of squirrels.
I complicated the model by adding 15 hunters to the landscape. Now, the model starts with 150 squirrels, 100 mountain lions, and 15 hunters. This model operates under the assumption that hunters want to kill mountain lions, who presumably try to eat the farm animals that represent the hunters' livelihoods. I made the mountain lion death rate dependent on the number of hunters, and the model changed such that the squirrel population exploded and the mountain lion population approached extinction every 20 years. I based this model on a real event, which took place and is still taking place in the Sierra Nevada. Squirrel populations there apparently reached record levels when farmers seeking to protect their land killed off the vast majority of the mountain lion population there. Now, hunters in the area kill squirrels for sport because they disrupted the food chain so irrevocably.
Este modelo busca simular la demanda y oferta de materiales de construcción en la ciudad de Calí (Colombia), En cuanto a la demanda se presenta como principales iniciadores entre otros:
La salud económica (PIB regional, desempleo, cartera hipotecaria)
Estado de la construcción (Licenciamientos, iniciaciones, obras civiles, despachos de cemento)
En cuanto a la oferta se presenta como principales iniciadores entre otros:
Capacidad de proveedores: (Disponibilidad de fuentes, Calidad)
From Jay Forrester 1988 killian lectures youtube video describing system dynamics at MIT. For more detailed biography See Jay Forrester memorial webpage For MIT HIstory see IM-184930 For Applications se IM-185462
A pest known as a grape-leaf hopper can cause considerable losses in vineyards. Periodically it was found that a natural parasite, anagrus epos, drastically reduced the size of the hopper population. This, in turn, led to a reduction in food (hoppers) available to the parasite and the parasite population declined until the hopper population increased again. This cycle would repeat.It was found that the parasite, anagrus epos, also feeds on a non-pest leaf hopper which feeds on blackberries. By planting small patches of wild blackberries in the vineyards, the growers were able to maintain a stable parasite population that was large enough to control population explosions of both leaf hoppers.
Format: Given pre-conditions when independent variables(s) then dependent variable
Given Earnings Decline (0.25), Spending Variance (55), Initial Investment (500) and Rate of Return (RandNormal(0.06, 0.12)) when one of these independent variables change then how sensitive is Investment (22) over a 30 year time period (-1,000)
H1: if you Earn more then Investment will last much longer => rejected
H2: if you Spend less then Investment will last much longer => accepted
H3: if your Initial Investment is higher then Investment will last much longer => accepted
H4: if you reduce your Spend when Investments are declining then Investment will last much longer => accepted
Given Earnings Decline (0.25), Spending Variance (55), Initial Investment (500) and Rate of Return (RandNormal(0.06, 0.12)) when one of these independent variables are optimised then Investment will last exactly 30 years by minimising the absolute investment gap
H1: if you set an appropriate Spending Base then remaining Investment is 0 => rejected
H2: if you set an appropriate Spending Reduction then remaining Investment is 0 => rejected
Source for investment returns:https://seekingalpha.com/article/3896226-90-year-history-of-capital-market-returns-and-risks
This is a model that simulates the competition between logging versus adventure tourism (mountain bike riding) in Derby Tasmania. The simulation is borrowed from the Easter island simulation
Based on model discussed by John D. Sterman (p 508) in All models are wrong: reflections on becoming a systems scientist (2002). Task: (A) Sketch what you think the resultant graph will be (see directions for drawing in model). (B) Then Run Simulation. Optional Extension: Replace Graph In/Out Flow connection with a connection from Trig. function. Repeat (A) & (B).
At first, I cloned the System Dynamics Model from the "Predator-Prey Interactions" tutorial. After I did this for populations of squirrels and mountain lions instead of moose and wolves, the model showed that the more squirrels mountain lions catch, the more the mountain lion population grows, and the squirrel population declines. The squirrel death rate, therefore, depends on the number of mountain lions and the mountain lion birth rate depends on the number of squirrels.
I complicated the model by adding 15 hunters to the landscape. Now, the model starts with 150 squirrels, 100 mountain lions, and 15 hunters. This model operates under the assumption that hunters want to kill mountain lions, who presumably try to eat the farm animals that represent the hunters' livelihoods. I made the mountain lion death rate dependent on the number of hunters, and the model changed such that the squirrel population exploded and the mountain lion population approached extinction every 20 years. I based this model on a real event, which took place and is still taking place in the Sierra Nevada. Squirrel populations there apparently reached record levels when farmers seeking to protect their land killed off the vast majority of the mountain lion population there. Now, hunters in the area kill squirrels for sport because they disrupted the food chain so irrevocably.
Format: Given pre-conditions when independent variables(s) then dependent variable
Given Earnings Decline (0.25), Spending Variance (55), Initial Investment (500) and Rate of Return (RandNormal(0.06, 0.12)) when one of these independent variables change then how sensitive is Investment (22) over a 30 year time period (-1,000)
H1: if you Earn more then Investment will last much longer => rejected
H2: if you Spend less then Investment will last much longer => accepted
H3: if your Initial Investment is higher then Investment will last much longer => accepted
H4: if you reduce your Spend when Investments are declining then Investment will last much longer => accepted
Given Earnings Decline (0.25), Spending Variance (55), Initial Investment (500) and Rate of Return (RandNormal(0.06, 0.12)) when one of these independent variables are optimised then Investment will last exactly 30 years by minimising the absolute investment gap
H1: if you set an appropriate Spending Base then remaining Investment is 0 => rejected
H2: if you set an appropriate Spending Reduction then remaining Investment is 0 => rejected
Source for investment returns:https://seekingalpha.com/article/3896226-90-year-history-of-capital-market-returns-and-risks
Based on model discussed by John D. Sterman (p 508) in All models are wrong: reflections on becoming a systems scientist (2002). Task: (A) Sketch what you think the resultant graph will be (see directions for drawing in model). (B) Then Run Simulation. Optional Extension: Replace Graph In/Out Flow connection with a connection from Trig. function. Repeat (A) & (B).
A Conveyor is essentially an infinite order exponential delay. This insight illustrates how increasing the order of an exponential delay begins to approximate a conveyor. The 10th order delay very closely aligns to the Delay 10 Conveyor.
At first, I cloned the System Dynamics Model from the "Predator-Prey Interactions" tutorial. After I did this for populations of squirrels and mountain lions instead of moose and wolves, the model showed that the more squirrels mountain lions catch, the more the mountain lion population grows, and the squirrel population declines. The squirrel death rate, therefore, depends on the number of mountain lions and the mountain lion birth rate depends on the number of squirrels.
I complicated the model by adding 15 hunters to the landscape. Now, the model starts with 150 squirrels, 100 mountain lions, and 15 hunters. This model operates under the assumption that hunters want to kill mountain lions, who presumably try to eat the farm animals that represent the hunters' livelihoods. I made the mountain lion death rate dependent on the number of hunters, and the model changed such that the squirrel population exploded and the mountain lion population approached extinction every 20 years. I based this model on a real event, which took place and is still taking place in the Sierra Nevada. Squirrel populations there apparently reached record levels when farmers seeking to protect their land killed off the vast majority of the mountain lion population there. Now, hunters in the area kill squirrels for sport because they disrupted the food chain so irrevocably.
A model which simulates the competition between logging versus adventure tourism (mountain bike ridding) in Derby Tasmania. Simulation borrowed from the Easter Island simulation.
How the model works.
Trees grow, we cut them down because of demand for Timber amd sell the logs.
With mountain bkie visits. This depends on past experience and recommendations. Past experience and recommendations depends on Scenery number of trees compared to visitor and Adventure number of trees and users. Park capacity limits the number of users.
Interesting insights
It seems that high logging does not deter mountain biking. By reducing park capacity, visitor experience and numbers are improved. A major problem is that any success with the mountain bike park leads to an explosion in visitor numbers. Also a high price of timber is needed to balance popularity of the park. It seems also that only a narrow corridor is needed for mountain biking
This model (starting with a clone of a previous project on squirrels, mountain lions, and hunters) is a simplified version using only rabbits and snakes.
By modifying the birth and death rates, the variations in population change dramatically. Interestingly, in this iteration, the populations reach dismal lows, but always pick up later.
