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About On Using Quasi-Newton Algorithms
This document describes using quasi-Newton algorithms of the Broyden class to correlate thermal models with test results. The approach reduces the number of iterations needed for model correlation by several orders of magnitude compared to other methods like genetic algorithms. It works by finding the parameter values that satisfy the equation of the calculated temperatures equaling the measured temperatures, rather than minimizing the difference between them. This allows the full vector of temperature differences to be evaluated at each step rather than a single error value. The Broyden's good method and a self-developed variant are tested on thermal models, showing correlation times reduced from weeks/months to hours/days.
Detailed Information
| Author: | ['a_ordanini4627'] |
|---|---|
| Publication Year: | 2018 |
| Pages: | 8 |
| Language: | English |
| Format: | |
| Price: | FREE |
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