Abstract The degree of uncertainty associated with the value a company plays relevant role in valuation analysis. We propose an original and robust methodology for market valuation, which replaces traditional point estimate conventional Discounted Cash Flow model probability distribution fair values that convey information about both expected its intrinsic uncertainty. Our depends on two main i...

The subject of uncertainty is a phenomenon that has been researched and discussed in order to make the market more predictable by providing balances historical process. Uncertainty an important determinant enterprise investment for all kinds markets, it effective at increasing decreasing levels depending on time events. However, due characteristics health services market, always considered as f...

Design of a logistics network in proper way provides a proper platform for efficient and effective supply chain management. This paper studies a multi-period, multi echelon and multi-product integrated forward-reverse logistics network under uncertainty. First, an efficient complex mixed-integer linear programming (MILP) model by considering some real-world assumptions is developed for the inte...

In this article, a novel approach for training deep neural networks using Bayesian techniques is presented. The methodology allows an easy evaluation of model uncertainty and, additionally, robust to overfitting. These are commonly the two main problems classical, i.e., non-Bayesian architectures have struggle with. proposed applies variational inference in order approximate intractable posteri...

This paper introduces the concept of safety-related (SR) uncertainty and the methodology to measure SR uncertainty. SR uncertainty is concerned with the effect of parameter uncertainty on the uncertainty of system unsafety (defined with respect to achieved safety integrity level), which is in direct contrast to the effect on overall system uncertainty. The properties of SR uncertainty are discu...