Create an Insight Maker account to start building models. Insight Maker is completely free.


Start Now

Insight Maker runs in your web-browser. No downloads or plugins are needed. Start converting your ideas into your rich pictures, simulation models and Insights now. Features

Simulate

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

Collaborate

Sharing models has never been this easy. Send a link, embed in a blog, or collaborate with others. It couldn't be simpler. More

Free & Open

Build your models for free. Share them with others for free. Harness the power of Insight Maker for free. Open code mean security and transparency. More


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.

Insight diagram
Without the conditional logic, this system is designed to be a stable equilibrium - no matter what N1 and N2 are set to initially, the model will always stabilize to N1 = 157 and N2 = 71. 

The conditional logic implements a grazing intervention rule.

Here, if the Buffalo Grass population exceeds a threshold density, a grazing pressure term is applied. This represents cattle grazing that preferentially removes Buffalo Grass once it becomes dominant. The idea of this model is to explore a rangeland management issue. 
Lotka-Volterra Competition With Conditional Logic
3 2 weeks ago
Insight diagram
Investigations into the relationships responsible for the success and failure of nations. This investigation was prompted after reading numerous references on the subject and perceiving that *Why Nations Fail: The Origins of Power, Prosperity, and Poverty* by Acemoglu and Robinson seem to make a great deal of sense.
@LinkedInTwitterYouTube
Why Nations Fail
Insight diagram
SARS-CoV-19 spread in different countries
- please adjust variables accordingly

Italy
  • elderly population (>65): 0.228
  • estimated undetected cases factor: 4-11
  • starting population size: 60 000 000
  • high blood pressure: 0.32 (gbe-bund)
  • heart disease: 0.04 (statista)
  • free intensive care units: 3 100

Germany
  • elderly population (>65): 0.195 (bpb)
  • estimated undetected cases factor: 2-3 (deutschlandfunk)
  • starting population size: 83 000 000
  • high blood pressure: 0.26 (gbe-bund)
  • heart disease: 0.2-0.28 (herzstiftung)
  • free intensive care units: 5 880

France
  • elderly population (>65): 0.183 (statista)
  • estimated undetected cases factor: 3-5
  • starting population size: 67 000 000
  • high blood pressure: 0.3 (fondation-recherche-cardio-vasculaire)
  • heart disease: 0.1-0.2 (oecd)
  • free intensive care units: 3 000

As you wish
  • numbers of encounters/day: 1 = quarantine, 2-3 = practicing social distancing, 4-6 = heavy social life, 7-9 = not caring at all // default 2
  • practicing preventive measures (ie. washing hands regularly, not touching your face etc.): 0.1 (nobody does anything) - 1 (very strictly) // default 0.8
  • government elucidation: 0.1 (very bad) - 1 (highly transparent and educating) // default 0.9
  • Immunity rate (due to lacking data): 0 (you can't get immune) - 1 (once you had it you'll never get it again) // default 0.4

Key
  • Healthy: People are not infected with SARS-CoV-19 but could still get it
  • Infected: People have been infected and developed the disease COVID-19
  • Recovered: People just have recovered from COVID-19 and can't get it again in this stage
  • Dead: People died because of COVID-19
  • Immune: People got immune and can't get the disease again
  • Critical recovery percentage: Chance of survival with no special medical treatment
SARS-CoV-19 model
Insight diagram
As initially proposed by Pr. William M White of Cornell University:

http://www.geo.cornell.edu/eas/education/course/descr/EAS302/302_06Lab11.pdf
http://www.eas.cornell.edu/
Global Carbon Cycle
Insight diagram
Safira Husnun Naza / 25/572327/PTK/17000

Model Dilantin yang dimodifikasi menjadi two-compartment repeated dose dengan kompartemen pencernaan dan plasma. Simulasi menunjukkan pola absorpsi dari pencernaan ke plasma serta konsentrasi plasma yang berada dalam rentang terapi.
Model Two-Compartment Repeated Dose Dilantin
Insight diagram
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