Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

This is a graphical user interface (GUI) application built with Python and Tkinter, designed to solve linear programming problems using SciPy's optimization library (linprog). Generates a plot of the ...

The objective of the 3D-SCALO problem is to assign the given components to optimal mounting surfaces and position them at the best locations, while satisfying the requirements for (1) heat dissipation ...

Standard computer implementations of Dantzig's simplex method for linear programming are based upon forming the inverse of the basic matrix and updating the inverse ...

The artificial intelligence start-up said the new system, OpenAI o3, outperformed leading A.I. technologies on tests that rate skills in math, science, coding and logic. By Cade Metz Reporting from ...

Proponents of generative AI have claimed that the technology can make human workers more productive, especially when it comes to writing computer code. If anything, the study says usage of Copilot ...

Many important practical computations, such as scheduling, combinatorial, and optimization problems, use techniques known as integer programming to find the best combination of many variables. In ...

This paper introduces the Julia programming language as a dynamic, cost-effective, and efficient framework for implementing structural analysis packages. To achieve this, the finite element method was ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...