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Date
Relevance
Modeling Scenario
387
views
398
downloads
0
comments
1-102-CancerTumor-ModelingScenario
This module guides students in the use of differential equation models to predict cancer growth and optimize treatment outcomes. Several classical models for cancer growth are studied, including exponential, power law, Bertalanffy, logistic, and...
optimization
logistic
prediction
data fitting
power law
Gompertz
cancer growth
eponential
Bertalanaffy
Modeling Scenario
256
views
227
downloads
0
comments
1-054-GrowthInFarmland-ModelingScenario
An enriching project developing a model from data with missing temporal information is described. Students fit functions to the data that leads to the creation of a differential equations model, which they then are required to analyze in multiple...
fitting
farm
farmland
Modeling Scenario
364
views
162
downloads
0
comments
1-001d-HotelPopulationDecay-ModelingScenario
You will be modeling the following situation: 100 people are in a hotel. Each day, each person has a random chance of 50% of leaving the hotel. No new people enter the hotel. Before you run the simulation in MATLAB, answer some questions.
simulation
logistic
exponential decay
fitting
Modeling Scenario
223
views
258
downloads
0
comments
6-029-TumorGrowth-ModelingScenario
This modeling scenario guides a student familiar with single ordinary differential equation (ODE) models towards the development of a more complex system of two ODEs for describing the evolution of tumor growth over time.
Pop_Growth Pilot
logistic
comparment
tumor
synthetic data
sum of squares error
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