Rastrigin function losses for . حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…"

Rastrigin function losses for . حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…"

Rosenbrock function losses for . حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…"

NRPStransformer, an Accurate Adenylation Domain Specificity Prediction Algorithm for Genome Mining of Nonribosomal Peptides حسب Zhihan Zhang (1403308)

"…Leveraging the sequences within the flavodoxin-like subdomain, we developed a substrate specificity prediction algorithm using a protein language model, achieving 92% overall prediction accuracy for 43 frequently observed amino acids, significantly improving the prediction reliability. …"

State Function-Based Correction: A Simple and Efficient Free-Energy Correction Algorithm for Large-Scale Relative Binding Free-Energy Calculations حسب Runduo Liu (10756379)

"…We present an efficient and straightforward State Function-based Correction (SFC) algorithm, which leverages the state function property of free energy without requiring cycle identification. …"

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

"…This penalty was proposed by Verzelen et al. and achieves optimal rates for changepoint detection and changepoint localization in a non-asymptotic scenario. Our proposed algorithm, Multiscale Functional Pruning Optimal Partitioning (Ms.FPOP), extends functional pruning ideas presented in Rigaill and Maidstone et al. to multiscale penalties. …"

The convergence curves of the test functions. حسب Ruiyu Zhan (21602031)

"…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …"

Single-peaked reference functions. حسب Ruiyu Zhan (21602031)

"…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …"

Optimization outcome for the Rosenbrock function. حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…"

Optimization outcome for the Rastrigin function. حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…"

2D Rastrigin function. حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…"

2D Levy function. حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…"

2D Rosenbrock function. حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…"

Optimization outcome for the Levy function. حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…"

Flowchart of the AH-NSAFSA. حسب Jihui Hu (19812736)

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Decoding process. حسب Jihui Hu (19812736)

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China medical waste disposal market size statistics and forecast, 2018 to 2029. حسب Jihui Hu (19812736)

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Levels of input parameters. حسب Jihui Hu (19812736)

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The S/N ratio plot of the AH-NSAFSA in the Taguchi methodology. حسب Jihui Hu (19812736)

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Tuned values of parameters. حسب Jihui Hu (19812736)

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