Code and data. by Shangyang Jin (21772466)

Subjects:

The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”

Comparison of different optimization algorithms. by Hang Zhao (143592)

Subjects:

Greedy optimization algorithm. by Alexis Bénichou (19832361)

Optimization-Driven Steganographic System Based on Fused Maps and Blowfish Encryption by Ahmed Aljughaiman (21793526)

Subjects:

data_code.zip by Mengmeng Gong (20129994)

“…In this study, we conduct an in-depth investigation of a novel adaptive covariance inflation algorithm (t-X) within the framework of an observation system simulation experiment (OSSE) based on anintermediate coupled model (ICM) and the Ensemble Adjustment KF(EAKF), aiming to develop a joint approach for optimizing both model parameters and initial fields simultaneously. …”

Pseudo-code of large neighborhood search (<i>LNS</i>) algorithm. by Jiren CAO (20442214)

Data and code resources. by Sam Hall-McMaster (10343795)

Subjects:

Data and code used in this article. by Yazhen Zhu (3595430)

Subjects:

code&data by Liyuan Liu (18298084)

“…It then developed a greedy heuristic algorithm based on the Gaussian Two-Step Floating Catchment Area method and Gini coefficient analysis for evaluating and optimizing facility accessibility and fairness. …”

Codes for high-order analytical continuation algorithms based on direct derivation and recursion methods by Jian Ma (19747060)

“…The optimal order of the analytical continuation algorithm is contingent upon the noise level of gravity data. …”

Source code. by Jesse Wheeler (18462457)

Subjects: “…routinely applicable algorithm…”

Code and data for "A reduced-scale adaptive morphing vehicle prototype with enhanced aerodynamic efficiency" by Peng Zhang (16789041)

“…<p dir="ltr">This dataset contains:</p><ul><li>CAD files for the design and fabrication of the proposed adaptive morphing vehicle prototype;</li><li>Computer programs for genetic-algorithm-based autonomous optimization;</li><li>Raw data acquired in the wind tunnel experiments for demonstrating and validating the morphing vehicle prototype and optimization algorithm; and</li><li>Computer codes for post-processing and visualizing raw data.…”

Performance of algorithms outside the training species. by Sven B. Gould (12237287)

A framework for improving localisation prediction algorithms. by Sven B. Gould (12237287)

“…Classifiers on which the algorithms are trained could include parameters such as the evolutionary distance of a species, non-coding regions, or a protein’s abundance as a currently neglected factor. …”

Coding schematic. by Dongyan Wang (195482)

“…To enhance the reliability of intercity railway operations and reduce spare parts management costs, this paper employs the Zebra Optimization Algorithm-Least Squares Support Vector Machine (ZOA-LSSVM) to analyze the reliability of the important Weibull distribution spare parts of the intercity railway and fit the parameters of the reliability function for spare parts. …”

Data and code used in this article. by Feng Shen (151470)

“…<div><p>In this study, the traditional lag structure selection method in the Mixed Data Sampling (MIDAS) regression model for forecasting GDP was replaced with a machine learning approach using the particle swarm optimization algorithm (PSO). The introduction of PSO aimed to automatically optimize the MIDAS model’s mixed-frequency lag structures, improving forecast accuracy and resolving the "forecast accuracy" and "forecast cost" weighting problem. …”

, MSE, and MAE of the optimised algorithms. by Itxasne Antúnez Sáenz (22794696)

The pseudo-code of the WOA-LSTM-PID model. by Dayu Zhang (710629)

“…To solve this problem, the study proposes an improved PID controller based on the Long Short-Term Memory (LSTM) optimized by the Whale Optimization Algorithm (WOA). …”

Flowchart of the SSA-based optimization of the BPNN algorithm. by Yeping Shi (14279118)

“…<p>Flowchart of the SSA-based optimization of the BPNN algorithm.</p>…”