This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

Experiment with adjusting the initial number of moose and wolves on the island.

Clusters of interacting methods for improving health services network design and delivery. Includes Forrester quotes on statistical vs SD methods and the Modeller's dilemma. Simplified version of IM-14982 combined with IM-17598 and IM-9773

This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

Experiment with adjusting the initial number of moose and wolves on the island.

based on Kolb 2005 article and 1984 publication on Experiential Learning and Pepper World Hypotheses via John Barton. See also The Art of the State IM  and Social Relations Worldviews IM  and The Educated Mind IM

In this model we seek to show how Formula 1 can bring there Co2 emissions down to zero by 2030 (six years from now).

2f. [thought question] Is it possible for r maxrmax to be positive and yet for the total regional abundance to exhibit a persistent declining trend? Explain your reasoning, using at least one biologically realistic example. You can use the agent-based metapopulation model in InsightMaker to help test your ideas, but this is not required.

From Werner Ulrich's JORS Articles Operational research and critical systems thinking – an integrated perspective. Part 1: OR as applied systems thinking. Journal of the Operational Research Society advance online publication (14 December 2011). and Part 2 :OR as argumentative practice.

See also insight on Boundary Critique

This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

WIP integration of dynamic and complexity insights using rubik's cube metaphor from Pop Health Book insight folders,  and others linked in notes

This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

MODEL EXPLANATION:

This model simulates possible crime patterns among the youth population of Bourke, where levels of alienation, policing and community engagement expenditure can be manipulated. Here the youth in Bourke have a minimum percentage of interest to participate in community activities in which the government aims to improve their lifestyle and therefore reduce the rate of criminal activity. ASSUMPTIONS:There are 1500 youths of Bourke in the population susceptible to committing crime and simulations of criminal tendencies are only based the factors presented, no external influences.
VARIABLES:“Alienation” includes any factors that can increase the likelihood of youths to commit crime such as exposure to domestic violence, household income, education level, and family background‘Community engagement Expenditure’ is the total monies budgeted into community activities to develop youths in and out of Juvenile detention‘Policing’ is the amount of police placed onto patrol in the town of Bourke to reinforce safety and that the law is abided by. STOCKS:Conviction rate is set to 60%A juvenile detention sentence for convicted criminals is set to 3 monthsThe top 30% of the most severe offenders are sent to rehabilitation for 3 months, to which they return to Bourke, assumingly in a better state and less likely to repeat a petty crimeCommunity activities are set to last for 3 months to align with the seasons: these could be sporting clubs or youth groupsCommunity participants have a 20% chance of being disengaged as it may not align with their interestsInvestments into policing are felt immediately& community engagement expenditure has a delay of 3 months
INTERESTING FINDS:1.    Alienation set to max (0.2), policing and community engagement set to minimum shows a simulation whereby all criminals are in town rather than being expedited and placed into juvenile detention, even after a base value of 200 youths placed into juvenile detention – this shows that budget is required to control the overwhelming number of criminal youths as they overrun Bourke2.    Set community activity to 0.01, policing to max & Alienation to max. A lack of community activity can produce high disengagement amongst youths regardless of police enforcement to the town of Bourke that has a high criminal rate. Juvenile detention only lasts for so long and not all youths can be rehabilitated, so they are released back into Bourke with chances of re-committing crime. 3.    Alienation plays a major role in affecting youths to consider committing crime. To keep criminal activity to a minimum, ideally the maximum rates of budget in policing and community engagement within youths highly at risk of committing crime should be pushed. Realistically, budget is a sensitive case within a small town and may not be practical. 4. Set policing to 0.25, community engagement to 0.2 & alienation to 0.04. Moderate expenditure to community activities and policing can produce high engagement rates and improved youths in the town of Bourke.

Assess how intake completion rates impact the efficiency of onboarding patients referred to TMH.

Completed

This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

The model is designed to provide a general understanding of the wear and tear on roads or a community's circulation system as a result of vehicle traffic generated by development within and outside of a community. It is not based on realistic assumptions regarding those impacts, it simply attempts to convey the flow of influence.

This model simulates the tradeoff between the total costs and total benefits of using AI. The model shows the investment rate in comparison to the effectiveness and efficiency rate of the AI and we can visualize this relationship with our graph to see the cost and benefits of AI.