Difference between revisions of "Team:SSHS-Shenzhen/Model"

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Our model is formalized by the Differential Equation: (Logistic Regression)</p>
 
Our model is formalized by the Differential Equation: (Logistic Regression)</p>
 
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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>
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The Logistic Regression (or the Logistic Model) is a model that is greatly practiced in the field of epidemics. In this case, we chose this model to figure out the relationship between GC content and RNAi efficiency. Instead of guessing a linear function between the two, the Logistic Model helps us to develop a better understanding of this critical parameter which isn't backed by scientific theories.
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The model works under the below assumptions:<br><br>
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Births and natural deaths are neglected<br>
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The beetles cannot recover by itself or with the help of the leaves<br>
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Other factors do not change throughout the experiment
 
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         <td>α</td>
 
         <td>α</td>
 
         <td>GC content</td>
 
         <td>GC content</td>
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        <td>β</td>
 
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        <td>Mortality. Mathematically it's the derivative of D.</td>
 
 
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Revision as of 18:11, 5 October 2018

Title

Title

Model

Abstract

Our model is formalized by the Differential Equation: (Logistic Regression)

The Logistic Regression (or the Logistic Model) is a model that is greatly practiced in the field of epidemics. In this case, we chose this model to figure out the relationship between GC content and RNAi efficiency. Instead of guessing a linear function between the two, the Logistic Model helps us to develop a better understanding of this critical parameter which isn't backed by scientific theories.

Assumptions

The model works under the below assumptions:

Births and natural deaths are neglected
The beetles cannot recover by itself or with the help of the leaves
Other factors do not change throughout the experiment

Parameters

Parameters Meaning
D(t) Number of deaths
η RNAi efficiency
α GC content

Experiments

Results