Skip to content

RMarkdowns and HTML output files about my final paper at UFRJ, which discusses the process of rockfalls on slopes in instability situation. Includes Data Analysis (DA) & Machine Learning (ML) codes.

Notifications You must be signed in to change notification settings

daiha98/rockfall

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

README

1. INTRODUCTION:

  • This markdown contains informations about a dataset that is related to the main parameters of rockfall in slopes and the risk that these events could cause. It's a small dataset with more than 1000 rows and 9 variables that the goal is to work with data analysis/visualization and machine learning algorithms to predict the target mean_range.

2. PROGRAMMING LANGUAGE:

  • This code was made on R, which is a language that is not entirely unlike (versions 3 and 4 of) the S language developed at AT&T Bell Laboratories by Rick Becker, John Chambers and Allan Wilks. R is free software distributed under a GNU-style copyleft. The core of R is an interpreted computer language with a syntax superficially similar to C, but which is actually a "functional programming language" with capabilities similar to Scheme. The language allows branching and looping as well as modular programming using functions.

3. ABOUT THE DATASET:

  • The 'rockfall' data frame dim contains 1050 rows and 9 variables:

    • ID = Index counter
    • h_enc = Slope height (m)
    • ang_enc = Slope angle (°)
    • rock_mass = Mass of the rock (kg)
    • vel_rad = Angular velocity of the rock (rad/s)
    • mean_range = Mean range value of the rock simmulated on Rocfall (m)
    • porc_ac = Rock percentage that falls on the 'Critic Area', according to CPRM mapping manual
    • porc_disp = Rock percentage that falls on the 'Dispersion Area', according to CPRM mapping manual
    • porc_rock_mapped = porc_ac + porc_disp'

About

RMarkdowns and HTML output files about my final paper at UFRJ, which discusses the process of rockfalls on slopes in instability situation. Includes Data Analysis (DA) & Machine Learning (ML) codes.

Topics

Resources

Stars

Watchers

Forks

Contributors