Flowchart of the new algorithm. by Jinyu Wang (381467)

“…<div><p>In recent years, various real-time processing methods have been developed for Satellite Laser Ranging (SLR) data. However, the recognition rate of the single-stage Graz filtering algorithm for high-orbit satellites is less than 1%, and traditional two-stage filtering algorithms, such as polynomial fitting and iterative filtering techniques, exhibit high false and missed detection rates. …”

Relevant Parameters. by Dongyan Wang (195482)

“…By comparing the fitting performance of several methods, including ZOA-LSSVM, Genetic Algorithm (GA)-LSSVM, LSSVM, and Least Squares Regression (LSR), the effectiveness of ZOA-LSSVM is validated. …”

Average computation time for each algorithm. by Jinyu Wang (381467)

“…<div><p>In recent years, various real-time processing methods have been developed for Satellite Laser Ranging (SLR) data. However, the recognition rate of the single-stage Graz filtering algorithm for high-orbit satellites is less than 1%, and traditional two-stage filtering algorithms, such as polynomial fitting and iterative filtering techniques, exhibit high false and missed detection rates. …”

Fitted density estimates under the clustering solution of the K⋅R model. by Koyel Majumdar (20416871)

Subjects:

Fitted density estimates under the K⋅R model on a simulated dataset. by Koyel Majumdar (20416871)

Subjects:

The CCCP algorithm of EQSVR based on ClipDCD. by Aiman Tahir (21485064)

Structure of the Kuhn-Munkres Algorithm. by Qingnan Ji (22662198)

Subjects:

Identification of early prognostic biomarkers in Severe Fever with Thrombocytopenia Syndrome using machine learning algorithms by Jie Zhu (126574)

“…Six different machine learning algorithms were employed to develop prognostic models based on the clinical features during the acute phase, which were reduced using Lasso regression.…”

Data Sheet 1_Development and validation of an endoscopic diagnostic model for sessile serrated lesions based on machine learning algorithms.docx by Xinying Yu (16400811)

“…Background and aims<p>Sessile serrated lesions (SSLs) are morphologically subtle and often misclassified as hyperplastic polyps (HPs), increasing colorectal cancer risks. We developed a machine learning (ML) model to improve endoscopic SSL diagnosis.…”

Silhouette scores for each clustering algorithm. by Zoïe W. Alexiou (21989297)

TOF dispersive data of the hard tissue-mimicking phantom fit with the KVFD model. by Jotham Josephat Kimondo (19139409)

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…Computational methods can efficiently narrow down the candidate targets for subsequent experimental validation. We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. …”

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…Computational methods can efficiently narrow down the candidate targets for subsequent experimental validation. We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. …”

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…Computational methods can efficiently narrow down the candidate targets for subsequent experimental validation. We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. …”

Fitting flow of DAKM algorithm. by Xiaobing Chen (572034)

Subjects:

Results of RF algorithm screening factors. by Jintao Li (448681)

The relevant data file for this article. by Linsha Liu (20378293)

Predicting CO₂ Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms by Zahra Bastami (21474755)

Predicting CO₂ Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms by Zahra Bastami (21474755)

Definitions of relevant SSA parameters. by Yeping Shi (14279118)

“…Response data are classified and regressed using a sparrow search algorithm (SSA)-optimized backpropagation neural network (BPNN). …”