https://github.com/gagniuc/markov-chains-vb6

Markov Chains in Visual Basic 6.0 (VB6) - These applications use transition matrices to make predictions by using a Markov chain. For exemplification, the values from the transition matrix, in any of the three applications, represent the transition probabilities between two states found in a sequence of observations.
https://github.com/gagniuc/markov-chains-vb6

markov-chain markov-model prediction vb6 weather weather-forecast

Last synced: 7 months ago
JSON representation

Markov Chains in Visual Basic 6.0 (VB6) - These applications use transition matrices to make predictions by using a Markov chain. For exemplification, the values from the transition matrix, in any of the three applications, represent the transition probabilities between two states found in a sequence of observations.

• Host: GitHub
• URL: https://github.com/gagniuc/markov-chains-vb6
• Owner: Gagniuc
• License: mit
• Created: 2021-11-03T23:28:28.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2022-11-18T12:08:50.000Z (almost 3 years ago)
• Last Synced: 2025-01-15T07:31:54.300Z (9 months ago)
• Topics: markov-chain, markov-model, prediction, vb6, weather, weather-forecast
• Language: Visual Basic 6.0
• Homepage:
• Size: 2.67 MB
• Stars: 5
• Watchers: 1
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE.md

Awesome Lists containing this project

README

          
# Markov Chains in VB6

These applications use transition matrices to make predictions by using a Markov chain. For exemplification, the values from the transition matrix, in any of the three applications, represent the transition probabilities between two states found in a sequence of observations (ex. s=SRSRSSRRRSRRSRRRS). These two states are: Sunny and Rainy, or R and S. Based on the initial probability vector, the application calculates how the weather may be on a number of days. More in-depth information on these matters can be found in the primary source.

# Screenshot

![screenshot](https://github.com/Gagniuc/Markov-Chains-VB6/blob/main/img/Markov%20Chains%20VB6%20(1).PNG)

![screenshot](https://github.com/Gagniuc/Markov-Chains-VB6/blob/main/img/Markov%20Chains%20VB6%20(2).PNG)

![screenshot](https://github.com/Gagniuc/Markov-Chains-VB6/blob/main/img/Markov%20Chains%20VB6%20(3).PNG)

# References

- Paul A. Gagniuc. Markov chains: from theory to implementation and experimentation. Hoboken, NJ,  John Wiley & Sons, USA, 2017, ISBN: 978-1-119-38755-8.