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Porovnání prediktorů / Comparing of predictorsJelínková, Hana January 2011 (has links)
No description available.
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Ignalinos AE tikimybinio saugos vertinimo modelio neapibrėžtumo ir jautrumo analizė / Uncertainty and sensitivity analysis of Ignalina NPP probabilistic safety assessment modelBucevičius, Nerijus 19 June 2008 (has links)
Neapibrėžtumo analizė techninių sistemų modeliavimo rezultatams yra ypač aktuali, kai modeliuojamas pavojingų sistemų darbas, saugą užtikrinančių sistemų funkcionavimas, nagrinėjami avarijų scenarijai ar kiti, su rizika susiję klausimai. Tokiais atvejais, ypatingai reaktorių saugos analizės srityje, yra labai svarbu, kad gauti modeliavimo rezultatais būtų robastiški. Šiame darbe yra atliekama Ignalinos AE tikimybinio saugos vertinimo modelio neapibrėžtumo ir jautrumo analizė. Neapibrėžtumo ir jautrumo analizė atlikta naudojantis skirtingais statistinio vertinimo metodais, taikant programų paketą SUSA. Gauti rezultatai palyginti su tikimybinio modeliavimo sistemos Risk Spectrum PSA tyrimo rezultatais. Palyginimas parodė, jog skirtingais metodais ir programiniais paketais parametrų reikšmingumas įvertintas vienodai. Statistinė neapibrėžtumo ir jautrumo analizė, taikant Monte Karlo modeliavimo metodą, leido nustatyti parametrus turėjusius didžiausią įtaką modelio rezultatui. / The uncertainty estimation is the part of full analysis for modelling of safety system functioning in case of the accident, for risk estimation and for making the risk-based decision. In this paper the uncertainty and sensitivity analysis of Ignalina NPP probabilistic safety assessment model was performed using SUSA software package. The results were compared with the results, performed using software package Risk Spectrumm PSA. Statistical analysis of uncertainty and sensitivity allows to estimate the influence of parameters on the calculation results and find those modelling parameters that have the largest impact on the result. Conclusions about for importance of a parameters and sensitivity of the result are obtained using a linear approximation of the model under analysis.
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Assessment Of Disruption Risk In Supply Chain The Case Of Nigeria’s Oil IndustryAroge, Olatunde O. January 2018 (has links)
evaluate disruption risks in the supply chain of petroleum production. This methodology is developed to formalise and facilitate the systematic integration and implementation of various models; such as analytical hierarchy process (AHP) and partial least squares structural equation model (PLS-SEM) and various statistical tests. The methodology is validated with the case of Nigeria’s oil industry.
The study revealed the need to provide a responsive approach to managing the influence of geopolitical risk factors affecting supply chain in the petroleum production industry. However, the exploration and production risk, and geopolitical risk were identified as concomitant risk factors that impact performance in Nigeria’s oil industry. The research findings show that behavioural-based mechanisms successfully predict the ability of the petroleum industry to manage supply chain risks. The significant implication for this study is that the current theoretical debate on the supply chain risk management creates the understanding of agency theory as a governing mechanism for supply chain risk in the Nigerian oil industry. The systematic approach results provide an insight and objective information for decisions-making in resolving disruption risk to the petroleum supply chain in Nigeria. Furthermore, this study highlights to stakeholders on how to develop supply chain risk management strategies for mitigating and building resilience in the supply chain in the Nigerian oil industry.
The developed systematic method is associated with supply chain risk management and performance measure. The approach facilitates an effective way for the stakeholders to plan according to their risk mitigation strategies. This will consistently help the stakeholders to evaluate supply chain risk and respond to disruptions in supply chain. This capability will allow for efficient management of supply chain and provide the organization with quicker response to customer needs, continuity of supply, lower costs of operations and improve return on investment in the Nigeria oil industry. Therefore, the methodology applied provide a new way for implementing good practice for managing disruption risk in supply chain. Further, the systematic approach provides a simplistic modelling process for disruption risk evaluation for researchers and oil industry professionals. This approach would develop a holistic procedure for monitoring and controlling disruption risk in supply chains practices in Nigeria.
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