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Updated: Jun 4, 2025

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扩展的PROMETHEE方法与 (p,q) -rung线性Diophantine模糊集用于机器人选择问题

J Vimala1, A N Surya1, Nasreen Kausar2

  • 1Department of Mathematics, Alagappa University, Karaikudi, Tamilnadu, 630003, India.

Scientific reports
|January 2, 2025
PubMed
概括

这项研究将 (p,q) -rung线性迪奥芬丁模糊集合与PROMETHEE方法集成,用于复杂的决策. 增强的框架改善了处理复杂的现实世界问题,通过机器人选择示例来证明这一点.

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相关概念视频

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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