Abstract: The dynamic optimal power flow (DOPF) is a mixed-integer nonlinear programming problem. This article builds a DOPF model with discrete and continuous variables, and then proposes the ...

Probability theory is indispensable in computer science: It is at the core of artificial intelligence and machine learning, which require decision making under uncertainty. It is integral to CS theory ...

Probability distribution is an essential concept in statistics, helping us understand the likelihood of different outcomes in a random experiment. Whether you’re a student, researcher, or professional ...

Cumulative probability is an essential concept in the world of statistics and probability theory. It refers to the likelihood that a random variable will take a value equal to or less than a specific ...

Leverage the power of data analysis, machine learning, and artificial intelligence with a specialized master’s degree in one of today’s most in-demand fields. Taught by experienced professionals, this ...

Abstract: An information-theoretic proof of a strengthened version of the classical discrete central limit theorem is presented. Using only information-theoretic and elementary arguments, convergence ...

Continuous-variable quantum key distribution offers simple, stable and easy-to-implement key distribution systems. The discrete modulation scheme further reduces the technical difficulty. The main ...