Search for dissertations about: "decision failure"
Showing result 1 - 5 of 170 swedish dissertations containing the words decision failure.
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1. Pipe failure assessment and decision support system for a smart operation and maintenance : A comprehensive literature review and a conceptual decision analysis model proposal
Abstract : The reported research provides a rough guide to the best practice of decision modeling concerning urban pipeline systems’ rehabilitation. The thesis aims to bring attention to the fact that a proper decision-making model is a cornerstone for efficient infrastructure management. READ MORE
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2. Predictive Health Monitoring for Aircraft Systems using Decision Trees
Abstract : Unscheduled aircraft maintenance causes a lot problems and costs for aircraft operators. This is due to the fact that aircraft cause significant costs if flights have to be delayed or canceled and because spares are not always available at any place and sometimes have to be shipped across the world. READ MORE
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3. After Firm Failure : Emotions, learning and re-entry
Abstract : Uncertainty is inherent to the entrepreneurship process. As such, the outcomes of entrepreneurial endeavors are unknown and unknowable a priori– some will be successful and others will fail. Entrepreneurship research, however, often focuses on new ventures and the entrepreneurs who own and run them in the start-up and growth phases. READ MORE
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4. Ethical Issues in Cardiology Patients' views of information and decision-making
Abstract : The over-riding aim of this thesis was to obtain a deeper understanding of the way patients with cardiac problems view both information related to their health and medical decisions and their role in decision-making processes. An important objective was to identify reasons why patients do not ask for or assimilate information or why they do not want or feel that they are able to influence medical decisions. READ MORE
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5. Learning Decision Trees and Random Forests from Histogram Data : An application to component failure prediction for heavy duty trucks
Abstract : A large volume of data has become commonplace in many domains these days. Machine learning algorithms can be trained to look for any useful hidden patterns in such data. Sometimes, these big data might need to be summarized to make them into a manageable size, for example by using histograms, for various reasons. READ MORE