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algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
algorithm demand » algorithm lennard (Expand Search), algorithm design (Expand Search), algorithm maml (Expand Search)
python function » protein function (Expand Search)
demand function » reward function (Expand Search), hand function (Expand Search), related function (Expand Search)
algorithm b » algorithm _ (Expand Search), algorithms _ (Expand Search)
b function » _ function (Expand Search), a function (Expand Search), 1 function (Expand Search)
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161
The Simulation and optimization process of pipe diameter selection.
Published 2022Subjects: “…evolutionary genetic algorithm…”
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Optional pipe diameter and unit price of NYN.
Published 2022Subjects: “…evolutionary genetic algorithm…”
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Optional pipe diameter and unit price of HN.
Published 2022Subjects: “…evolutionary genetic algorithm…”
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Algorithm results based on FE simulated likelihood functions.
Published 2020“…<p>(A) Nodule depth estimation by the algorithm with the likelihood functions obtained by FEM simulation. …”
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173
Practical rules for summing the series of the Tweedie probability density function with high-precision arithmetic
Published 2019“…With these practical rules, simple summation algorithms provide sufficiently robust results for the calculation of the density function and its definite integrals. …”
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Load curves of residential and IT sector loads with CS algorithm based DSM.
Published 2024Subjects: -
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Flowchart of DAPF-RRT algorithm.
Published 2025“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”
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177
Performance comparison of different algorithms.
Published 2025“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”
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