Conventional risk assessment frameworks usually define risk as a function of vulnerabilities and threats, but they frequently lack a single quantitative model that incorporates the unique features of each element. In order to close this gap, this paper creates a flexible, open, and theoretically...

-- Analysis of Factors Affecting Goodwill Impairment and Research on Models Assisted by Computer Vision -- The Impact of Financial Technology Innovation on New Quality Productive Forces -- Empirical Study on Digital Finance Empowering the High Quality Development of Urban Ecological Economy in...

Traditional electrical grid as the largest and most complex industry in the world is currently under fundamental development. According to the IEEE Std1547.4, large distribution systems can be clustered into a number of micro-grids (MGs) to facilitate the control and operation infrastructure in...

Traditional electrical grid as the largest and most complex industry in the world is currently under fundamental development. According to the IEEE Std1547.4, large distribution systems can be clustered into a number of micro-grids (MGs) to facilitate the control and operation infrastructure in...

Predicting human behavior from a small amount of training examples is a challenging machine learning problem. In this thesis, we introduce the principle of maximum causal entropy, a general technique for applying information theory to decision-theoretic, game-theoretic, and control settings...

Wind tunnel test measurements to characterize the static lift and drag coefficients of airfoils used in wind turbine blades are shown to possess large uncertainties, which leads to uncertainties in the aerodynamic loads on the rotor. In this paper a rational stochastic model is proposed to...