Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

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Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. by Gursimran Singh (575288)

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Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

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<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

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Function graph and algorithm iterative graph. by WanRu Zhao (18980374)

“…The IERWHO algorithm is an improved Wild Horse optimization (WHO) algorithm that combines the concepts of chaotic sequence factor, nonlinear factor, and inertia weights factor. …”

Code snippets to add user-specific custom functionality in PyNoetic. by Gursimran Singh (575288)

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Mean convergence graphs of the evolution in the performance function and its terms through generations in thirty executions of each algorithm. by Roberto Castro-Medina (21484990)

“…<p>Mean convergence graphs of the evolution in the performance function and its terms through generations in thirty executions of each algorithm.…”

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. …”

Algorithm flow of BBO. by Jian Yang (12136)

“…<div><p>The stable and site-specific operation of transmission lines is a crucial safeguard for grid functionality. This study introduces a comprehensive optimization design method for transmission line crossing frame structures based on the Biogeography-Based Optimization (BBO) algorithm, which integrates size, shape, and topology optimization. …”

Performance comparison of mainstream algorithms. by Junjie Lu (160350)

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Efficient algorithms to discover alterations with complementary functional association in cancer by Rebecca Sarto Basso (6728921)

“…We propose a combinatorial formulation for the problem, and prove that the associated computational problem is computationally hard. We design two algorithms to solve the problem and implement them in our tool UNCOVER. …”

Route for bays29 output by ABSQL algorithm. by Jin Zhang (53297)

“…DSRABSQL builds upon the Q-learning (QL) algorithm. Considering its problems of slow convergence and low accuracy, four strategies within the QL framework are designed first: the weighting function-based reward matrix, the power function-based initial Q-table, a self-adaptive <i>ε-beam</i> search strategy, and a new Q-value update formula. …”

FAR-1: A Fast Integer Reduction Algorithm Compared to Collatz and Half-Collatz by Faizan Ali (21689861)

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Reward function related parameters. by Honglei Pang (22693724)

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Example of landmark registration to align ‘peaks’ of high density in the probability density function (PDF) of CD4 expression on blood T cells for a target distribution and chosen... by Ross J. Burton (10941910)

Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements by Pascal Wang (10130612)

“…<div>This directory contains Python 3 scripts implementing the Trajectory Adaptive Multilevel Sampling algorithm (TAMS), a variant of Adaptive Multilevel Splitting (AMS), for the study of rare events. …”

MOEA/D-ND algorithm flowchart. by Jun Sun (48981)

“…Therefore, an improved multi-objective optimization algorithm proposed by decomposition is introduced to optimize its matching network to achieve overall optimization design of power amplifiers. …”

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

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Comparative analysis of algorithms. by Xumin Zhao (18261643)

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