Row precision vs. Aggregation errors: MAP is the best way to use "greedy" functions like AND or OR in a single, dynamic ...

Imagine Jo: Everyone in Jo's life recognizes her as an outstanding problem solver. She's the type of person who seems capable of almost anything. Jo excels at intuitive problem-solving. Over her life, ...

Abstract: The article discusses the development and study of a new matrix-based hybrid genetic algorithm (MBHGA) for solving an agent-based model of firms’ behavior with controlled trade interactions.

Analog computers are systems that perform computations by manipulating physical quantities such as electrical current, that map math variables, instead of representing information using abstraction ...

If you use Excel 40 hours a week (and those are the weeks you are on vacation), welcome to the MrExcel channel. Home to 2,400 free Excel tutorials. Bill "MrExcel" Jelen is the author of 67 books about ...

Abstract: Recently, analog matrix inversion circuits (INV) have demonstrated significant advantages in solving matrix equations. However, solving large-scale sparse tridiagonal linear systems (TLS) ...

Q. I work with large spreadsheets. These spreadsheets have hundreds or even thousands of rows and often 10 or more columns. It’s so much to process that I become confused and make mistakes. Does Excel ...

There are tough problems that every business faces, and they can slow things down, make budgets stretch, or put off decisions. It takes time to deal with these problems, and most businesses don’t have ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The great challenge in teaching analytical chemistry today is to ensure the learning ...

COLUMBUS, Ohio (WCMH) – The Columbus Division of Police is reporting its homicide solve rate for the year is at 78% — nearly 30% above the national average. The department said part of what is helping ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...