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Data Visualization Of Urban Water Demand Analysis Using Machine learning

Hersi, Ibrahim

The goal of the project is to visualise patterns of urban development in a visually engaging interactive map. The goal is to develop a statistical model to predict underground water resources and water consumption in different buildings in the city of Uppsala. To achieve the goal, we use machine learning algorithms on a dataset of buildings in Uppsala. The thesis consists of three parts; first and foremost, we discuss the importance of data visualisation in machine learning and developing a visually engaging map that shows the relationship between underground water resources and urban buildings. In the second part, we explain the used machine learning algorithms more in-depth and how they were used to predict water consumption in urban buildings. In the last part, we predict the building type, for example, apartments,house, from a dataset of unknown buildings.

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Data Visualization Of Urban Water Demand Analysis Using Machine learning

Hersi, Ibrahim

The goal of the project is to visualise patterns of urban development in a visually engaging interactive map. The goal is to develop a statistical model to predict underground water resources and water consumption in different buildings in the city of Uppsala. To achieve the goal, we use machine learning algorithms on a dataset of buildings in Uppsala. The thesis consists of three parts; first and foremost, we discuss the importance of data visualisation in machine learning and developing a visually engaging map that shows the relationship between underground water resources and urban buildings. In the second part, we explain the used machine learning algorithms more in-depth and how they were used to predict water consumption in urban buildings. In the last part, we predict the building type, for example, apartments,house, from a dataset of unknown buildings.

Data Visualization Of Urban Water Demand Analysis Using Machine learning

Hersi, Ibrahim

The goal of the project is to visualise patterns of urban development in a visually engaging interactive map. The goal is to develop a statistical model to predict underground water resources and water consumption in different buildings in the city of Uppsala. To achieve the goal, we use machine learning algorithms on a dataset of buildings in Uppsala. The thesis consists of three parts; first and foremost, we discuss the importance of data visualisation in machine learning and developing a visually engaging map that shows the relationship between underground water resources and urban buildings. In the second part, we explain the used machine learning algorithms more in-depth and how they were used to predict water consumption in urban buildings. In the last part, we predict the building type, for example, apartments,house, from a dataset of unknown buildings.

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Titel:

Data Visualization Of Urban Water Demand Analysis Using Machine learning

Beteiligte:

Hersi, Ibrahim (Autor:in)

Erscheinungsdatum:

01.01.2020

Anmerkungen:

IT

Medientyp:

Hochschulschrift

Format:

Elektronische Ressource

Sprache:

Englisch

Schlagwörter:

Engineering and Technology , Teknik och teknologier

Klassifikation:

DDC: 720

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