CEC2017 benchmark function experiment results(dim = 30). by Qingwen Meng (156386)

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CEC2017 benchmark function experiment results(dim = 100). by Qingwen Meng (156386)

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WSN optimized by different algorithms. by Qingwen Meng (156386)

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Compare algorithm parameter settings. by Qingwen Meng (156386)

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Impact of POMCP parameters on the estimated value function. by Benoîte de Saporta (20454662)

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Risk function of the controlled continuous time PDMP. by Benoîte de Saporta (20454662)

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A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finit... by Hassan Mehboob (8960273)

Registration phase. by Khondokar Oliullah (21553289)

Comparison the results with and without Fourier Loss Function for Rain100H. by Chaobing Zheng (20896579)

Multidimensional test results of BWEMFO and MFO on IEEE CEC 2017 test functions. by Jingjing Ma (419752)

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

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Evaluating and Improving Light Absorption Retrievals of Black Carbon Using In Situ Polar Nephelometry by Qizhi Xu (1729057)

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

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Framework of the proposed algorithm. by Jia Li (160557)

Comparison between the proposed framework with and without Fourier Loss Function for Rain100H. by Chaobing Zheng (20896579)

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

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Coati optimization algorithm for brain tumor identification based on MRI with utilizing phase-aware composite deep neural network by Rajesh Kumar Thangavel (20591164)

“…In this research, Utilizing Phase-aware Composite Deep Neural Network Optimized with Coati Optimized Algorithm for Brain Tumor Identification Based on Magnetic resonance imaging (PACDNN-COA-BTI-MRI) is proposed. …”

Pseudocode of the BBAC_I Algorithm. by Zezhi Lin (22521663)

Execution Steps of the EOF Algorithm. by Zezhi Lin (22521663)

Predicting the Mutagenic Activity of Nitroaromatics Using Conceptual Density Functional Theory Descriptors and Explainable No-Code Machine Learning Approaches by Andrés Halabi Diaz (20798460)

“…This study integrates conceptual density functional theory (CDFT) descriptors with explainable no-code machine learning (ML) models to predict NA mutagenicity based on Ames test results. …”