A Neutrosophic SuperHyper Number Framework for Accurate Statistical Evaluation of Financial Performance in High-Tech Enterprises [PDF]
Neutrosophic Sets and SystemsThis paper introduces a new mathematical model that evaluates the financial performance of high-tech enterprises using neutrosophic numbers and superhyper uncertainty theory. Traditional financial analysis often fails to address incomplete, indeterminate,
Yujuan Xie
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Ambiguity and uncertainty in Ellsberg and Shackle [PDF]
This paper argues that Ellsberg’s and Shackle’s frameworks for discussing the limits of the (subjective) probabilistic approach to decision theory are not as different as they may appear.
Carlo Zappia, Marcello Basili
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Dynamic optimization method for statistics of dry density of earth-rockfill materials
Yantu gongcheng xuebaoA method for optimizing the compaction quality control index of dams is proposed. Using the collected dry density of field soil samples, the statistics (mean, standard deviation and correlation distance) are determined.
JIA Yufeng 1, 2, FENG Wenquan 1, 2, CHI Shichun 1, 2
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Model uncertainty for the capacity of strip footings under negative and general combined loading [PDF]
, 2015 This paper investigates the model uncertainty of Eurocode 7 approach for estimating the bearing capacity of shallow foundations under negative and general combined loading.
Phoon, K. K., Tang, Chong
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Shackle versus Savage: non-probabilistic alternatives to subjective probability theory in the 1950s [PDF]
G.L.S Shackle’s rejection of the probability tradition stemming from Knight's definition of uncertainty was a crucial episode in the development of modern decision theory.
Carlo Zappia, Marcello Basili
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New statistical metliods in risk assessment by probability bounds [PDF]
, 2009 In recent years, we have seen a diverse range of crises and controversies concerning food safety, animal health and environmental risks including foot and mouth disease, dioxins in seafood, GM crops and more recently the safety of Irish pork.
Montgomery, Victoria
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Improper Priors via Expectation Measures
StatsIn Bayesian statistics, the prior distributions play a key role in the inference, and there are procedures for finding prior distributions. An important problem is that these procedures often lead to improper prior distributions that cannot be normalized
Peter Harremoës
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Decision under Uncertainty : the Classical Models [PDF]
This chapiter of a collective book is dedicated to classical decision models under uncertainty, i.e. under situations where events do not have "objective" probabilities with which the Decision Marker agrees. We present successively the two main theories,
Michèle Cohen +2 more
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Computational engineering design under uncertainty: an aircraft conceptual design perspective [PDF]
, 2009 Presented in this thesis is a novel methodology for aircraft design optimization in the presence of uncertainty, with emphasis on the conceptual design stage.
Padulo, Mattia
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Mean of Ratios or Ratio of Means: statistical uncertainty applied to estimate Multiperiod Probability of Defaul [PDF]
, 2014 The estimate of a Multiperiod probability of default applied to residential mortgages can be obtained using the mean of the observed default, so called the Mean of ratios estimator, or aggregating the default and the issued mortgages and computing the ratio of their sum, that is the Ratio of means.
openaire +2 more sources