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Dynamic Modeling with Java Adrian Trunzo Use the arrow keys or press the left mouse button to proceed through the slides.

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Presentation on theme: "Dynamic Modeling with Java Adrian Trunzo Use the arrow keys or press the left mouse button to proceed through the slides."— Presentation transcript:

1 Dynamic Modeling with Java Adrian Trunzo Use the arrow keys or press the left mouse button to proceed through the slides.

2 What is Dynamic Modeling? Dynamic modeling is the process of mathematically representing the state of a system (i.e. a population) over time. For my product I decided to create a computer program using Java technology to aid in the creation and use of these models.

3 Here we can see the basic properties of the model – the variables. There are two types of variables: the state variables, which act as stocks that are added to and subtracted from, and the control variables that manipulate the state variables.

4 Through their math definitions, all of the variables of the model are related to each other and form a web of connections. For this simple model, which defines the dynamics of a disease throughout a population, the links are fairly clear.

5 Once the variables of the model have been defined there are a number of evaluations that can be performed to further understand our system, such as a graph. For the simple disease model, we can see that the population susceptible to the disease and the number infected will cycle, but eventually stabilize.

6 How can Dynamic Models help? These models can help us to understand something we do not readily perceive. Through assuming certain conditions, we can also use dynamic models to predict certain occurrences. For my model, I chose to study and adapt a known insect population model to a gypsy moth population that I researched.

7 My population model is a four stage model, defining the four stages of the moth life: Egg, Larva, Pupa, and Adult.

8 Here is a layout view of model, showing the relationships between the variables.

9 A population without limitations will grow exponentially or very quickly. Gypsy moth populations are very susceptible to disease at high densities. By building a disease factor into the model, we can see that the population would fluctuate over time.

10 Restart


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