This paper mainly studies the configuration and scheduling optimization problem of integrated energy systems. Firstly, a mathematical model of the integrated energy system ... Finally, the ...

Maximum Likelihood Estimation is a fundamental statistical method used to estimate model parameters by maximizing ... particularly in parametric modeling and probabilistic approaches. Gradient Descent ...

The Bayesian method ... with my mathematical background, it took me three straight-days of reading examples and trying to put the pieces together to understand the methods. There was simply not enough ...

This course has 1 mandatory assignment that must be approved before you can sit the final exam. It will also be counted as one of the three attempts to sit the exam for this course, if you sit the ...

Computational optimization methods have matured over the last few years due to extensive research by applied mathematicians and engineers. These methods have been applied to many practical ...

A case study demonstrates the practical utility and advantages of our method, showcasing how probabilistic fuzzy rankings can provide more robust and transparent decision-making support compared to ...

This volume contains extended versions of 28 carefully selected and reviewed papers presented at The Fourth International Conference on Mathematical Methods in Reliability in Santa Fe, New Mexico, ...

Mar. 26, 2025 — Researchers have developed 'tomoseqr' -- a new software tool that enables easy estimation of the three-dimensional (3D) spatial distribution of gene expression. Tomoseqr is free ...