Algorithm of model development and validation. by Bethan Cracknell Daniels (20469396)

Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

Landslide susceptibility maps of the study area were developed using the RF algorithm for (a) post-Ketsana, (b) post-Podul, and (c) post-Molave periods. by Raja Das (1841107)

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

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

Subjects: “…crayfish optimization algorithm…”

Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Flowchart of DQN algorithm. by Jiandong Qiu (20389944)

The algorithm to define the study population. by Michael C. Reed (6622226)

Patient selection algorithm. by Dwi Kisworo Setyowireni (22656144)

Risk element category diagram. by Yao Hu (3479972)

“…This article extracted features related to risk assessment, such as weather factors, airport facility inspections, and security check results, and conducted qualitative and quantitative analysis on these features to generate a datable risk warning weight table. This article used these data to establish an LSTM model, which trained LSTM to identify potential risks and provide early warning by learning patterns and trends in historical data. …”

The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”

Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40). by Johannes Weyer (13392175)

Overview of the development of the biomarkers in the motor, exteroceptive, interoceptive, and cerebral domains. by Marialuisa Gandolfi (8639238)

Subjects:

Supporting data for “Developing algorithms to optimize recommender system for self-regulated learning promotion in online contexts: a design-based study” by Long Zhang (11129139)

Example measurement and analysis units for landscape elements. by Jaewon Han (8660295)

Subjects:

Scatter diagram of different principal elements. by Jizhong Wang (7441697)

“…<div><p>A fault diagnosis method for oil immersed transformers based on principal component analysis and SSA LightGBM is proposed to address the problem of low diagnostic accuracy caused by the complexity of current oil immersed transformer faults. Firstly, data on dissolved gases in oil is collected, and a 17 dimensional fault feature matrix is constructed using the uncoded ratio method. …”

Data Sheet 1_Predicting the risk of gastroparesis in critically ill patients after CME using an interpretable machine learning algorithm – a 10-year multicenter retrospective study.xlsx by Yuan Liu (88411)

“…</p>Methods<p>We gathered 34 feature variables from a cohort of 1,097 colon cancer patients, including 87 individuals who developed gastroparesis post-surgery, across multiple hospitals, and applied a range of machine learning algorithms to construct the predictive model. …”

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.…”

Plots showing Mean Decrease in Accuracy of the three landslide susceptibility models developed using the RF algorithm for the (a) post-Ketsana, (b) post-Podul, and (c) post-Molave periods. by Raja Das (1841107)