The algorithm for the same-day surgery protocol. by Magnus Tveit (11442200)

Left: the algorithm’s best estimate of where to put breakpoints for each number of breakpoints considered. by Zhengtian Li (5076704)

Ms.FPOP: A Fast Exact Segmentation Algorithm with a Multiscale Penalty by Arnaud Liehrmann (10970682)

“…Our proposed algorithm, Multiscale Functional Pruning Optimal Partitioning (Ms.FPOP), extends functional pruning ideas presented in Rigaill and Maidstone et al. to multiscale penalties. …”

Knowledge graph model rating function. by Chunjuan Li (7890182)

In this example the MPC algorithm perfectly tracks the noisy signal , which results in many false spikes. by Nicholas A. Rondoni (21573261)

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Algorithm Parameter Setting. by Tong Zhou (3770)

“…This strategy uses the improved D3QN algorithm combined with the excellent smoothness of the sine function to evaluate driving safety, helping vehicles find suitable gaps in traffic flow. …”

Algorithm operation steps. by Junyan Wang (4738518)

“…To address these issues, this paper proposes an improved object detection algorithm named SCI-YOLO11, which optimizes the YOLO11 framework from three aspects: feature extraction, attention mechanism, and loss function. …”

Artificial colony algorithm flow. by Jianpeng Zhang (528185)

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Pseudo-code of ABC algorithm. by Jianpeng Zhang (528185)

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IEEE CEC 2017 benchmark function specifications. by Kankan Tang (21474968)

IEEE CEC 2022 benchmark function specifications. by Kankan Tang (21474968)

Comparison of compression rates of DDQR and Geco3 using simulated data around the region where the performance of DDQR exceeds that of GeCo3. by Yujun Wang (1947196)

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Pipeline of the interactor algorithm. by Jose Cleydson F. Silva (8685594)

Fig 1 - by Yuh-Chin T. Huang (17867207)

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Optimization results of different algorithms. by Haijian Wang (746739)

“…Subsequently, the constraint conditions and objective functions were determined. Moreover, the multi-objective genetic algorithm optimized the structural block brake design. …”

Parameters of the test function. by Yiqiong Gao (16698968)

“…The proposed IFPA-ELM model for pipeline defect identification effectively overcomes the tendency of FPA to converge to local optima and that of ELM to engage in overfitting, which cause poor recognition accuracy. The identification rates of various pipeline defects by the IFPA-ELM algorithm are 97% and 96%, which are 34% and 13% higher, respectively, than those of FPA and FPA-ELM. …”

The precision (fraction of detected epidemics are indeed epidemics) and recall (the rate at which we claim an epidemics in the case of an epidemic) as a function of the percentile... by David Harvey (405930)

Parameter settings for metaheuristic algorithms. by Junhao Wei (6816803)

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An expectation-maximization algorithm for finding noninvadable stationary states. by Robert Marsland (8616483)

“…<p><i>(a)</i> Noninvadable states by definition can only exist in the region Ω of resource space where the growth rate <i>dN</i>_<i>i</i>/<i>dt</i> of each species <i>i</i> is zero or negative. …”

Using synthetic data to test group-searching algorithms in a context where the correct grouping of species is known and uniquely defined. by Yuanchen Zhao (12905580)

“…(C) We use the synthetic data as input for three families of regression-based algorithms: the EQO of Ref. [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012590#pcbi.1012590.ref026" target="_blank">26</a>] (which groups species into two groups), and two families we call K-means and Metropolis (see text), which can return any specified number of groups. …”