Search for dissertations about: "Lund data mining"
Showing result 1 - 5 of 9 swedish dissertations containing the words Lund data mining.
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1. Bringing predictability into a geometallurgical program : An iron ore case study
Abstract : The risks of starting, operating and closing mining projects have become higher than ever. In order to stay ahead of the competition, mining companies have to manage various risks: technical, environmental, legal, regulatory, political, cyber, financial and social. Some of these can be mitigated with the help of geometallurgy. READ MORE
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2. Mineralogical, chemical and textural properties of the Malmberget iron deposit : a process mineralogically characterisation
Abstract : This thesis combine two different but closely connected disciplines in a mining process to each other, ore geology and process mineralogy by studying mineralogical-textural features of the ore and the ore concentrate in an apatite iron ore deposit in Malmberget, Sweden. Apatite iron ore deposits (Kiruna type) exist in a few places around the world and the two most important deposits are mined by LKAB at Kiruna and Malmberget. READ MORE
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3. Towards reliable seismic hazard assessment in underground mines
Abstract : Seismic hazard is used for national, regional, and local level to ensure safe constructions in specific areas. In the mining industry this information is valuable e.g. to design infrastructure or rock support, to reduce the risk of rock burst and to minimise the risk of locating personnel in hazardous areas. READ MORE
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4. When Employees Leap to Self-Employment
Abstract : The dissertation studies the determinants of self-employment entry through an economics of entrepreneurship lens, and examines two sources of data: 7 years of employer--employee matched panel data and a laboratory experiment. The results suggest that employees are more likely to take the leap to self-employment when they have their own business idea, and are employed in occupations with high wage variance. READ MORE
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5. Use of data mining and artificial intelligence to derive public health evidence from large datasets
Abstract : This thesis explores the use of data mining and AI-tailored frameworks for extracting public health evidence from large health datasets. The research presented in this thesis demonstrates the potential of these tools for automating and simplifying the data mining process, and for providing valuable insights into various public health issues. READ MORE