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Predicting the hour of the day using machine learning tools
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Journal of Computer Science & Systems Biology

ISSN: 0974-7230

Open Access

Predicting the hour of the day using machine learning tools


Joint Event on 5th World Machine Learning and Deep Learning Congress and World Congress on Computer Science, Machine Learning and Big Data

August 30-31, 2018 Dubai, UAE

Nwachukwu Anthony Chukwuemeka

University of Ibadan, Nigeria

Posters & Accepted Abstracts: J Comput Sci Syst Biol

Abstract :

Imagine being able to tell the time of the day given information available in the neighborhood. Can machine learning be applied in solving this problem? This paper employed various machine learning models in making the best prediction of the hour of the day. Specific objects were identified in a neighborhood and images of these objects were captured in an open space over the 24 hours of the day including the images of the sky, temperature, humidity, noise intensity and other factors for these 24 hours period for many days. These were used to train the models with the various machine learning models made available in MATLAB. The model with the best prediction was chosen. An application user interface (GUI) was designed with MATLAB which makes the users experience great and was deployed to be used in windows and Java devices.

Biography :

E-mail: nwachukwu.anthony2017@gmail.com

 

Google Scholar citation report
Citations: 2279

Journal of Computer Science & Systems Biology received 2279 citations as per Google Scholar report

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