Parameters of each algorithm.

<div><p>Titanium alloy is known for its low thermal conductivity, small elastic modulus, and propensity for work hardening, posing challenges in predicting surface quality post high-speed milling. Since surface quality significantly influences wear resistance, fatigue strength, and corro...

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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Nanqi Li (11640083) (author)
مؤلفون آخرون:	ZuEn Shang (20571104) (author), Yang Zhao (39052) (author), Hui Wang (30400) (author), Qiyuan Min (20571107) (author)
منشور في:	2025
الموضوعات:	Medicine Biotechnology Evolutionary Biology Ecology Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified titanium alloy based small elastic modulus population initialization employs original static mechanism optimizing food quantity low thermal conductivity enhancing service performance enhancing population diversity 7 percent increase improve surface quality orthogonal matrix strategy ensure continuous prediction response surface method surface roughness strategy fusion proposed method prediction model work hardening ti64 compared speed milling posing challenges paper proposes objective equation local optima higher fitness generating individuals fatigue strength established using corrosion resistance convergence speed accelerating convergence
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Parameters of each algorithm.

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