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System Dynamics Models

System Dynamics is a powerful approach for modeling change within systems and Insight Maker is perfect for building System Dynamics models.

Agent Based Models

Explore the interactions between dynamic agents. Use Insight Maker to define agent behavior and simulate a population of agents interacting.

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Explore powerful simulation algorithms for System Dynamics and Agent Based Modeling. Use System Dynamics to gain insights into your system and Agent Based Modeling to dig into the details. Types of Modeling

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Explore What Others Are Building

Here is a sample of public Insights made by Insight Maker users. This list is auto-generated and updated daily.

This model is a classic instance of an Erlang Queuing Process.

We have the entities:

- A population of cars which start off in a "cruising" state;

- At each cycle, according to a Poisson distribution defined by "Arrival Rate" (which can be a constant, a function of time, or a Converter to simulate peak hours), some cars transition to a "looking" for an empty space state.

- If a empty space is available (Parking Capacity > Count(FindState([cars population],[parked]))) then the State transitions to "Parked."

-The Cars stay "parked" according to a Normal distribution with Mean = Duration and SD = Duration / 4

- If the Car is in the state "Looking" for a period longer than "Willingness to Wait" then the state timeouts and transitions to impatient and immediately transitions to "Crusing" again.

The model is set to run for 24 hours and all times are given in hours (or fraction thereof)

WIP:

- Calculate the average waiting time;

- Calculate the servicing level, i.e., 1- (# of cars impatient)/(#cars looking)

A big THANK YOU to Scott Fortmann-Roe for helping setup the model's framework.

Electric Car Parking

Ray Madachy

STEM-SM combines a simple ecosystem model (modified version of VSEM; Hartig et al. 2019) with a soil moisture model (Guswa et al. (2002) leaky bucket model). Outputs from the soil moisture model influence ecosystem dynamics in three ways.

(1) The ratio of actual transpiration to maximum evapotranspiration (T/ETmax) modifies gross primary productivity (GPP).

(2) Degree of saturation of the soil (Sd) modifies the rate of soil heterotrophic respiration.

(3) Water limitation of GPP (by T/ETmax) and of soil nutrient availability (approximated by Sd) combine with leaf area limitation (approximated by fraction of incident photosynthetically-active radiation that is absorbed) to modify the allocation of net primary productivity to aboveground and belowground parts of the vegetation.

Ecosystem dynamics in turn influence flows of water in to and out of the soil moisture stock. The size of the aboveground biomass stock determines fractional vegetation cover, which modifies interception, soil evaporation and transpiration by plants.

References:

Guswa, A.J., Celia, M.A., Rodriguez-Iturbe, I. (2002) Models of soil moisture dynamics in ecohydrology: a comparative study. Water Resources Research 38, 5-1 - 5-15.

Hartig, F., Minunno, F., and Paul, S. (2019). BayesianTools: General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics. R package version 0.1.7. https://CRAN.R-project.org/package=BayesianTools

Simple Terrestrial Ecosystem Model - Soil Moisture (STEM-SM)

Lisa Belyea

226

Basic model of Newton's mechanics applied to fall with air friction (e.g. an air balloon)

Ff prop v*v

Fall of a balloon in air

Hans Niedderer

5 5 months ago

From Schluter et al 2017 article A framework for mapping and comparing behavioural theories in models of social-ecological systems COMSeS2017 video. See also Balke and Gilbert 2014 JASSS article How do agents make decisions? (recommended by Kurt Kreuger U of S)

Modelling human behaviour (MoHuB)

Geoff McDonnell

La situación modelada expresa el crecimiento de las ventas impulsadas por la motivación y productividad, pero es frenada por el tamaño del nicho de mercado.

Límite de Crecimiento

Marcelo A. Castro Iglesias

610

Simplified system dynamics model of the global carbon cycle. The model represents carbon exchange among four aggregated reservoirs: atmosphere, terrestrial biosphere, surface ocean, and deep ocean. Fossil fuel emissions enter the atmosphere as an external forcing, while internal flows redistribute carbon between the atmosphere, land, surface ocean, and deep ocean. The model is intended to explore transient behavior, natural carbon sinks, atmospheric carbon persistence, and the long-term regulating role of the ocean.

0GlobalCarbonBalanceExpAtmOcean

Carlos Campuzano Calvo

3 3 weeks ago