First published 9/29/2026, 7:00:15 PM · Last updated 9/29/2026, 7:00:15 PM

Parameter identification of Preisach hysteresis model based on enhanced run global optimization algorithm with parallel architecture

A journal article published by Emerald on 2026-08-13 describes a method to identify parameters of the Preisach hysteresis model using an enhanced global optimization algorithm implemented with parallel architecture. No additional methodological details or results were included in the supplied source fields.

Categories: science-and-space, technology

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Confidence: 4/10How certain the assessment is based on the clarity and evidence in the cited reporting.
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Global importance: 2/10The event's broader significance, from limited importance (1) to major global importance (10).
Impact magnitude: 2/10The scale or severity of the real-world impact, from minor (1) to extreme (10).
Positivity: 5/10How harmful or beneficial the event is, from strongly harmful (1) to strongly positive (10).
Urgency: 1/10How time-sensitive the event is, from low urgency (1) to immediate attention needed (10).

Why it matters

The paper presents a methodological contribution to parameter identification for a hysteresis model that may be relevant to researchers in modeling and control.

Sources

Parameter identification of Preisach hysteresis model based on enhanced run global optimization algorithm with parallel architecture

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