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Streamer Social Media Virality 6

Alexander St. John

9 9 months ago

Policy Simulations

LeeGray

4

Working model of Yellowstone dynamics created by students in Ecology 2015 at McDaniel College. This class collaboration is the first attempt by these students to develop a functioning model that includes competition, disease, predation, invasives and impacts of environmental variables on the major species over the last 30 years.
Although we are attempting to create a realistic model, we are not researchers and depend on varied data sources for coefficients.

Eco15 Yellowstone Model

Esther

14

Addition of multilevel system dynamics to the context mechanism outcome realist evaluation framework of Pawson and Tilley. See also multilevel holons IM-3546

Realist Evaluation Dynamics

Geoff McDonnell

3

Simulate an impact of an asteroid of any Diameter at any given Speed!

Asteroid impact simulator

Alex Neroni

3

Marketing cost model

Streamer Social Media Virality 7

Alexander St. John

11 months ago

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

Formula 1 Model

Yasamin Osmani

Inference Robustness Assessment entails demonstrating that the ways a model differs from the real world do not affect model based inferences. From Jim Koopman's work on Infection Transmission Science esp Biological Networks Book Ch 13 p 453-4 and this accessible paper pdf

Inference Robustness Assessment

Geoff McDonnell

Final Group Formula 1 Model

Abdurehman Ahmad

4

The ecosystem of a game park can be made more realistic by introducing financial allocation for active game park quality upgrades, and to reduce the negative results of a high tourist influx. The total amount of money collected is a variable that is dependent on the number of tourists coming to a park until the number levels off at a state of maximum tourist congestion

A model of management decisions with cash reinvestment

Shoeb Hussain

A combination of qualitative and quantitative methods for implementing a systems approach, including virtual intervention experiments using computer simulation models. See also Complex Decision Technologies IM

Interventions and leverage points added in IM-1400 (complex!)

Systems Methods

Geoff McDonnell

3

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.

A decent match to the data is made with
Wolf Death Rate = 0.15
Wolf Birth Rate Factor = 0.0203
Moose Death Rate Factor = 1.08
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 MBR*M*(1-M/K)
Moose death flow is MDRF*Sqrt(M*W)
Wolf birth flow is WBRF*Sqrt(M*W)
Wolf death flow is WDR*W

A More Realistic Model of Isle Royale: Predator Prey Interactions

Andrew E Long

83

Documentation

The Insight shown demonstrates how demand and supply in a real estate market can affect pricing.

Demand, Supply and Price have been represented by stocks. Each has an inflow where it has an increase in stock, and a corresponding outflow where stock is decreased.

Linking each stock and flow is a variable that changes that which it is linked to. These have been labelled appropriately. Each variable takes a decimal value and multiplies it with that it is linked to, such as the rate of demand affecting the price set as 0.001*Demand. This is to generate the loops required to show the rise and fall in price, demand and supply.

Adjustments can be made to the price, supply and demand stocks to simulate different scenarios. Price can be between 400 (400,000) and 1000 (1,000,000) in accordance to average housing prices. Demand and supply can be between 0 (0%) and 100 (100%), although having these set as realistic figures will demonstrate the simulation best.

Each simulation can be focused on how either demand and price interact over time or supply and price. These are shown in different tabs.

When the simulation is carried out, the way in which demand and supply rates affect pricing can be seen. Demand and supply are shown with price following shortly after with a slight delay, since changes in market behavior does not immediately affect prices of housing.

It should also be noted that the lines that represent each stock do not directly reflect the prices of housing in reality. Prices do not fluctuate so rapidly from 400 to near 0 like they do on the graph, however these are just representations of the interactions between each stock in a marketplace.

Zachary Chapman - 43309399 - Assignment 3 Final

Zachary Chapman

3

Based on a book chapter by Rosemarie Sadsad based on her PhD Thesis. See also other Insights tagged Multiscale and Realist ( IM-3546 and IM-3834 are embedded here)

Multiscale modeling process

Geoff McDonnell

A launchpad to tie together some ideas about Reality. See wikipedia

Reality

Geoff McDonnell

4 months ago

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.

Day 22: More Realistic Model of Isle Royale: Predator Prey Interactions

Jacob Englert

Attempts to model in the social dynamics of returning players

Streamer Social Media Virality 7 w Player loop

Alexander St. John

3 9 months ago

Simulation d'un MRU d'un corps qui avance avec une régulation de vitesse réaliste.

serie 08a ex4 Une regulation de vitesse plus realiste V1

Bernard2018

Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.

With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.

We start with an SIR model, such as that featured in the MAA model featured in

https://www.maa.org/press/periodicals/loci/joma/the-sir-model-for-spread-of-disease-the-differential-equation-model

Without mortality, with time measured in days, with infection rate 1/2, recovery rate 1/3, and initial infectious population I_0=1.27x10-4, we reproduce their figure

With a death rate of .005 (one two-hundredth of the infected per day), an infectivity rate of 0.5, and a recovery rate of .145 or so (takes about a week to recover), we get some pretty significant losses -- about 3.2% of the total population.

Resources:

http://www.nku.edu/~longa/classes/2020spring/mat375/mathematica/SIRModel-MAA.nb
https://www.maa.org/press/periodicals/loci/joma/the-sir-model-for-spread-of-disease-the-differential-equation-model

Coronavirus: A Simple SIR (Susceptible, Infected, Recovered) with death

Andrew E Long

62