uncertainty modeling

Detection of Hidden Venture Risks: Analysis of Contradictory Data for Investors

The venture capital and startup market is a critical driver of innovation and technological progress in the modern economy. However, evaluating early-stage startups (Seed, Series A) faces significant challenges due to high uncertainty, a lack of reliable historical financial data, and the presence of conflicting qualitative evidence. Traditional methods, such as SWOT analysis and discounted cash flow (DCF) models, are often descriptive, static, or reliant on unverified assumptions, making them inadequate for quantitative risk assessment in such environments.

Robust shape optimization using artificial neural networks based surrogate modeling for an aircraft wing

Aerodynamic shape optimization is a very active area of research that faces the challenges of highly demanding Computational Fluid Dynamics (CFD) problems, optimization with Partial Differential Equations (PDEs) as constraints, and the appropriate treatment of uncertainties.  This includes the development of robust design methodologies that are computationally efficient while maintaining the desired level of accuracy in the optimization process.  This paper addresses aerodynamic shape optimization problems involving uncertain operating conditions.  After a review of pos