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− | Our model is formalized by the Differential Equation: (Logistic | + | Our model is formalized by the Differential Equation: (Logistic Regression)<br><br> |
− | We've chosen this model as it's often used for modeling the growth and decay of a population. In our condition where we apply our pesticide to the pests, we investigate the underlying | + | We've chosen this model as it's often used for modeling the growth and decay of a population. In our condition where we apply our pesticide to the pests, we investigate the underlying factors that affect the relationship between time and the number of deaths. |
</p> | </p> | ||
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Parameters | Parameters | ||
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− | < | + | <center> |
− | + | <table border="1"> | |
− | </ | + | <tr> |
+ | <td>Parameter</td> | ||
+ | <td>Meaning</td> | ||
+ | </tr> | ||
+ | <tr> | ||
+ | <td>D(t)</td> | ||
+ | <td>Number of deaths</td> | ||
+ | </tr> | ||
+ | <tr> | ||
+ | <td></td> | ||
+ | <td></td> | ||
+ | </tr> | ||
+ | </table> | ||
+ | </center> | ||
<h1> | <h1> |
Revision as of 17:43, 5 October 2018
Abstract
Our model is formalized by the Differential Equation: (Logistic Regression)
We've chosen this model as it's often used for modeling the growth and decay of a population. In our condition where we apply our pesticide to the pests, we investigate the underlying factors that affect the relationship between time and the number of deaths.
Assumptions
Parameters
Parameter | Meaning |
D(t) | Number of deaths |
Experiments
Results