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1	Machine learning for risk ranking of component failure : A comparative study of traditional- and survival machine learning approaches applied to historical data Nilsson, Fredrik, Fristedt, Fanny January 2023 (has links) This master thesis investigates the use of machine learning for predicting and assessing the risk of railway vehicle component failures. Data used for failure prediction often comes with limitations due to the complex nature of maintenance or sometimes requires investments for the extraction of information. Instead of real-time data, historical data and failure timestamps, easily accessed by organisations, are examined to see if they have the potential to contribute to a more effective maintenance strategy. Datasets used in maintenance often contain censored data and to overcome this problem survival machine learning models were also examined. Therefore both traditional machine learning models and survival machine learning models were evaluated and compared based on their C-index value. The results demonstrate that the survival machine learning models, which incorporate the risk and time-to-event aspects of the data, performed better than the traditional ones regarding the risk ranking of components. Random survival forest had the best result, and a ranking of important features. These findings indicate that there is a potential for survival machine learning, applied to existing historical data used for risk assessment for components failure. Machine learning Survival analysis Trains Freight trains Damage prediction Maskininlärning överlevnadsanalys tåg godståg Skadeprediktion Computer Sciences Datavetenskap (datalogi)
2	PSYKOSOCIALA FAKTORERS PÅVERKAN PÅ SKADERISKEN BLAND UNGDOMSLANDSLAGSSPELARE I FOTBOLL / Psychosocial factors influence on injuries among youth national soccer players Hulander, Markus January 2010 (has links) Syftet med denna studie har varit att studera psykosociala faktorers påverkan på skaderisken hos ungdomslandslagsspelare i fotboll. Tvångsmässig passion är en central faktor som studerats i relation till skada. Även faktorerna antal träningstimmar per vecka, antal spelade matcher, stress, själförtroende och motivation har studerats i relation till skada. En kvantitativ design har använts där 300 svenska ungdomslandslagsspelare i fotboll ingått som undersökningsdeltagare. Använda mätinstrument i undersökningen har varit PANAS, PSS, Grit-scale, PCLDS, Passion Scale, SCI samt SMS. Resultaten visade att män ådrar sig fler allvarliga skador (minst 4 veckors frånvaro) än kvinnor. Vidare visade resultaten att flergångsskadade spelare har en signifikant högre tvångsmässig passion än andra spelare. Resultaten diskuteras i förhållanden till uppsatsens teoretiska ramverk samt resultat från tidigare forskning. Förslag för framtida forskning inom området ges. / The purpose of this study was to study psychosocial factors influence on injury risk among youth national team soccer players. Obsessive passion has been a key factor that has been studied in relation to injury. Also the factors number of training hours per week, number of matches played, stress, self confidence and motivation has been studied in relation to injury. A quantitative design was used in which 300 Swedish youth national team soccer players have concluded as study participants. Used instruments in this survey has been PANAS, PSS, Grit-scale, PCLDS, Passion Scale, SCI and SMS.. The results showed that men incur more serious injuries then women. Furthermore, results showed that players with more than one injury during the season had higher obsessive passion then other players. The results are discussed in relation to the theoretical framework and the results from previous research. Proposal for future research in the field are provided. Soccer Football psychosocial factors injuries injury prevention passion stress national players Fussball Fußball Psychosozialen faktoren Verletzungen Schaden Leidenschaft Länderspiele Fotboll psykosociala faktorer skador skadeprediktion tvångsmässig passion stress landslagsspelare. Applied psychology Tillämpad psykologi Psychology Psykologi Sports Idrott Sports research Idrottsforskning

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Machine learning for risk ranking of component failure : A comparative study of traditional- and survival machine learning approaches applied to historical data

PSYKOSOCIALA FAKTORERS PÅVERKAN PÅ SKADERISKEN BLAND UNGDOMSLANDSLAGSSPELARE I FOTBOLL / Psychosocial factors influence on injuries among youth national soccer players