Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Process parameter optimization of Friction Stir Welding on 6061AA using
  Supervised Machine Learning Regression-based Algorithms   The highest strength-to-weight ratio criterion has fascinated curiosity
increasingly in virtually all areas where heft reduction is indispensable.
Lightweight materials and their joining processes are also a recent point of
research demands in the manufacturing industries. Friction Stir Welding (FSW)
is one of the recent advancements for joining materials without adding any
third material (filler rod) and joining below the melting point of the parent
material. The process is widely used for joining similar and dissimilar metals,
especially lightweight non-ferrous materials like aluminum, copper, and
magnesium alloys. This paper presents verdicts of optimum process parameters on
attaining enhanced mechanical properties of the weld joint. The experiment was
conducted on a 5 mm 6061 aluminum alloy sheet. Process parameters; tool
material, rotational speed, traverse speed, and axial forces were utilized.
Mechanical properties of the weld joint are examined employing a tensile test,
and the maximum joint strength efficiency was reached 94.2%. Supervised Machine
Learning based Regression algorithms such as Decision Trees, Random Forest, and
Gradient Boosting Algorithm were used. The results showed that the Random
Forest algorithm yielded highest coefficient of determination value of 0.926
which means it gives a best fit in comparison to other algorithms.

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The categories of this paper are: nucl-th
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The categories of this paper are: atom-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: physics
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The categories of this paper are: quant-ph
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The categories of this paper are: nlin
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The categories of this paper are: dg-ga
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The categories of this paper are: cmp-lg
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The categories of this paper are: bayes-an
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The categories of this paper are: math
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The categories of this paper are: adap-org
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The categories of this paper are: eess
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The categories of this paper are: ao-sci
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The categories of this paper are: chem-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: funct-an