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rainfall

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ApnaAnaaj aims to solve crop value prediction problem in an efficient way to ensure the guaranteed benefits to the poor farmers. The team decided to use Machine Learning techniques on various data to came out with better solution. This solution uses Decision Tree Regression technique to predict the crop value using the data trained from authentic datasets of Annual Rainfall, WPI Index for about the previous 10 years. This implementation proved to be promising with 93-95% accuracy.

  • Updated Apr 23, 2019
  • HTML

Existing precipitation prediction models have high error rates. The goal of this research is to reduce the error rates of the existing prediction models. An ensemble approach has been proposed to develop a New Aggregated Model to predict precipitation based on the dataset of some existing prediction models. This is a part of my master's thesis project.

  • Updated Nov 27, 2018
  • Python
intensity_duration_frequency_analysis

heavy rain as a function of the duration and the return period acc. to DWA-A 531 (2012) This program reads the measurement data of the rainfall and calculates the distribution of the rainfall as a function of the return period and the duration for duration steps up to 12 hours (and more) and return period in a range of '0.5a <= T_n <= 100a'

  • Updated May 5, 2021
  • Jupyter Notebook

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