Datathon Telenor Solution – Game of Prediction (GoP)

Posted 3 CommentsPosted in Datathons Solutions

The objective of this analysis is to find out the ravens that are not reaching the destination on time. This kind of analysis would help us to scrutinize and understand the towers(ravens) who would require our utmost attention, in order to improve the reasons which are playing a major role in the delays.
The data-set talks about the networks between the towers (ravens). The land based communication happens with the help of signals.
A cellular network or mobile network is a communication network where the last link is wireless. This wireless transmission is done by a tower which comprises of a transmitter and a receiver (for the wireless transmission). The channel provides transmission for both the data as well as Voice transmission.
Every cellular network has different set of frequencies, to avoid any kind of overlapping and interference. Despite of many precautions for maintaining the setup, there are few parameters that are still impacting the transmission. Few parameters can be classified as:
 Infrastructure
 Interference between the frequencies
 Climatic conditions
 External Factors (Predators etc.)
For this our first approach is to create a “Decision Model” which can help us to give value to our business and help in improving the communication.
****** The tools that we using in order to predict is ******
1. Visual Analysis using different plots
2. Usage of ARMA (Auto-regressive- Moving- Average- Model)
The usage of this Decision Model will help us in forecasting the failure rate for next 4-7 days in regards to the Ravens.

Datathon Kaufland Solution – LSTM and EDM Models for Predictive Maintenance

Posted 3 CommentsPosted in Datathons Solutions

In this paper we propose the use of a combination of LSTM and EDM models to address the issue of anomaly classification and prediction in time series data. Working with sensor data for automated storage and retrieval systems for a German hypermarket chain, we show that predictors based on variance and median methods show sufficient promise in the handling of anomalies.

Datathon Air Sofia Solution – Team Teljapenosss

Posted 3 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 […]

Datathon NSI Mentors’ Guidelines – Economic Time Series Prediction

Posted 1 CommentPosted in GD2018 Mentors, Mentors

In this article the mentors give some preliminary guidelines, advice and suggestions to the participants for the case. Every mentor should write their name and chat name in the beginning of their texts, so that there are no mix-ups with the other menthors. By rules it is essential to follow CRISP-DM methodology (http://www.sv-europe.com/crisp-dm-methodology/). The DSS […]

Datathon Telenor Mentors’ Guidelines – On TelCo predictions

Posted Leave a commentPosted in GD2018 Mentors, Mentors

In this article the mentors give some preliminary guidelines, advice and suggestions to the participants for the case. Every mentor should write their name and chat name in the beginning of their texts, so that there are no mix-ups with the other menthors. By rules it is essential to follow CRISP-DM methodology (http://www.sv-europe.com/crisp-dm-methodology/). The DSS […]

Datathon Sofia Air Mentors’ Guidelines – On IOT Prediction

Posted Leave a commentPosted in GD2018 Mentors, Mentors

In this article the mentors give some preliminary guidelines, advice and suggestions to the participants for the case. Every mentor should write their name and chat name in the beginning of their texts, so that there are no mix-ups with the other menthors. By rules it is essential to follow CRISP-DM methodology (http://www.sv-europe.com/crisp-dm-methodology/). The DSS […]

Datathon Kaufland Mentors’ Guidelines – On Predictive Maintenance

Posted Leave a commentPosted in GD2018 Mentors, Mentors

In this article, the mentors give some preliminary guidelines, advice, and suggestions to the participants for the case. Every mentor should write their name and chat name at the beginning of their texts so that there are no mix-ups with the other mentors. By rules, it is essential to follow CRISP-DM methodology (http://www.sv-europe.com/crisp-dm-methodology/). The DSS […]

Datathon Ontotext Mentors’ Guidelines – Text Mining Classification

Posted Leave a commentPosted in GD2018 Mentors, Mentors

In this article the mentors give some preliminary guidelines, advice and suggestions to the participants for the case. Every mentor should write their name and chat name in the beginning of their texts, so that there are no mix-ups with the other menthors. By rules it is essential to follow CRISP-DM methodology (http://www.sv-europe.com/crisp-dm-methodology/). The DSS […]