https://github.com/francescocoding/tsunami-damage-prediction-model
🌊 Probabilistic model that allows you to calculate the amount of damage (GBP) a tsunami can cause, given its characteristics.
https://github.com/francescocoding/tsunami-damage-prediction-model
Last synced: 4 months ago
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🌊 Probabilistic model that allows you to calculate the amount of damage (GBP) a tsunami can cause, given its characteristics.
- Host: GitHub
- URL: https://github.com/francescocoding/tsunami-damage-prediction-model
- Owner: FrancescoCoding
- Created: 2021-07-26T16:44:10.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2022-08-28T01:26:55.000Z (almost 3 years ago)
- Last Synced: 2025-01-04T00:51:27.672Z (6 months ago)
- Language: R
- Homepage:
- Size: 761 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Tsunami Damage Prediction Model 🌊
### Probabilistic model that calculates damage (GBP) caused by tsunamis, given their characteristics.
This project required me to formulate, research and present a mathematical and probabilistic model of attributes relating to a computer simulation with a team of 4 (me included) people.
In this team project, I had to choose, research and define a set of random variables representing a problem feature within a computer-based simulation of a real-life system or phenomenon.
For each random variable, we had to construct an appropriate probabilistic model of the distribution of values that the variable can take and to implement a means in R of randomly generating values for each variable;
Most of the RGN properties created in this model are based on the historical tsunamis dataset you find in this repo [Dataset >](https://github.com/FrancescoCoding/Tsunami-Damage-Prediction-Model/blob/main/tsunami_dataset.csv).
### This team project has enabled me to work on several skills, including:
- Coordinating and leading group sessions to coordinate advancement.
- Formulating a **probabilistic model** illustrated by random samples that accurately match the corresponding model.
- Research and define each attribute of the model rigorously and combined them in a coherent manner.
- Utilizing ggPlot2 for visualizing data
- Utilizing the team management **Agile** framework including:
- A **Sprint Planning** meeting at the start of each team session
- One or more **Scrum meetings** throughout the sessions to communicate progress and coordinate activity
- A **Sprint Review** meeting at the end of the session before each member leaves
## Some of the implementations of the damage prediction model:
### Water Depth
### Predicting Damage
### Overall Model
### Final output with the predicted damage
### Specific tsunami prediction
### Latitudes and Longitudes in the dataset visualized by Magnitude with ggPlot2
