Search for dissertations about: "Big Data Analytics"
Showing result 1 - 5 of 33 swedish dissertations containing the words Big Data Analytics.
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1. Big Data Analytics for Fault Detection and its Application in Maintenance
Abstract : Big Data analytics has attracted intense interest recently for its attempt to extract information, knowledge and wisdom from Big Data. In industry, with the development of sensor technology and Information & Communication Technologies (ICT), reams of high-dimensional, streaming, and nonlinear data are being collected and curated to support decision-making. READ MORE
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2. Smart Cities and Big Data Analytics : A Data-Driven Decision-Making Perspective
Abstract : The phenomenon of digitalization has led to the emergence of a new term—big data. Big data refers to the vast volumes of digital data characterized by its volume, velocity, variety, veracity, and value. READ MORE
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3. How can data science contribute to a greener world? : an exploration featuring machine learning and data mining for environmental facilities and energy end users
Abstract : Human society has taken many measures to address environmental issues. For example, deploying wastewater treatment plants (WWTPs) to alleviate water pollution and the shortage of usable water; using waste-to-energy (WtE) plants to recover energy from the waste and reduce its environmental impact. READ MORE
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4. Big Data Analytics for eMaintenance : Modeling of high-dimensional data streams
Abstract : Big Data analytics has attracted intense interest from both academia and industry recently for its attempt to extract information, knowledge and wisdom from Big Data. In industry, with the development of sensor technology and Information & Communication Technologies (ICT), reams of high-dimensional data streams are being collected and curated by enterprises to support their decision-making. READ MORE
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5. Data-Centric Network of Things : A Method for Exploiting the Massive Amount of Heterogeneous Data of Internet of Things in Support of Services
Abstract : Internet of things (IoT) generates massive amount of heterogeneous data, which should be efficiently utilized to support services in different domains. Specifically, data need to be supplied to services by understanding the needs of services and by understanding the environment changes, so that necessary data can be provided efficiently but without overfeeding. READ MORE