Monthly Challenge – Sofia Air – Solution – [iseveryonehigh]

Posted 8 CommentsPosted in Prediction systems

I have just begun my machine learning course from Andrew Ng at Coursera so I thought that this challenge would be a good test of my learnings. I apologise for the delay for article writing as I was not sure if I should have taken this challenge or not since the dataset seemed difficult to […]

Monthly Challenge – Sofia Air – Solution – Kung Fu Panda

Posted 12 CommentsPosted in Prediction systems

1. Business Understanding The air quality in Sofia, Bulgaria, has been a problem for some time already. The population of the city is constantly increasing and this brings more traffic on the streets. The car ownership in Sofia is among the highest in Europe with around 600 cars per 1000 citizens. Another huge issue in […]

Monthly Challenge – Sofia Air – Solution – Jacob Avila

Posted 8 CommentsPosted in Prediction systems

Preliminary Analisys Due to the objective focused on predicting air quality forecast for the next 24 hours per station, first step should be data understanding for citizen science air quality measurements to group it by station and summarize them by day. To complete this task for inspection and pre-processing in order to find missing data, outliers and […]

Datathon Sofia Air Solution – Air station measurement bias correction using Pearson correlation coefficient

Posted 5 CommentsPosted in Datathons Solutions

This article aims to improve the estimation of the measured PM10 pollutants. In Sofia, there are several air pollution measurement stations. They measure PM10 particles, which are particles found in the air with a diameter between 2.5 and 10 micrometers.

The measurement stations fall into two categories, official stations and citizen stations. The official stations provide reliable measurements, they are better monitored and documented. The down-side is that they are only 5 and they are all concentrated in a single region. The citizen stations represent devices mounted on people homes or properties which measure PM10 particles. There is a whole network of such devices. They are many in number and provide a good coverage of the city. The problem with those measurements is that they are biased because of many local factors. Therefore the measurements form the citizen stations are not as reliable as those from the official stations, but on the up-side they are many in numbers.

In this article we define a method to reduce the bias of the measurements from the citizen stations.

Datathon Air Sofia Solution – Team Teljapenosss

Posted 5 CommentsPosted in Prediction systems

— Team Teljapenosss Team Members — Jalapeno (Nasiba Zokirova) Team Mentor: petya-par   Business Understanding The levels of air pollution allegedly caused by solid fuel heating and motor vehicle traffic are ever growing in the City of Sofia. The primary economical impact for the City of Sofia was a ruling by the European Court of […]

Monthly Challenge – Sofia Air – Solution – Banana

Posted 11 CommentsPosted in Prediction systems

Business Understanding Air pollution is one of the major global topics in every part of the modern life – politics, ecology, social responsibility etc. In the last few years it became a major topic for Bulgaria and especially for Sofia. It is a well – known fact that our capital’s air is rather polluted. The […]